Overview

Dataset statistics

Number of variables43
Number of observations3009
Missing cells74255
Missing cells (%)57.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1011.0 KiB
Average record size in memory344.0 B

Variable types

Numeric16
Categorical24
Unsupported2
Boolean1

Warnings

Timestamp has a high cardinality: 2009 distinct values High cardinality
City has a high cardinality: 183 distinct values High cardinality
Position has a high cardinality: 148 distinct values High cardinality
Years of experience in Germany has a high cardinality: 53 distinct values High cardinality
Your main technology / programming language has a high cardinality: 274 distinct values High cardinality
Other technologies/programming languages you use often has a high cardinality: 562 distinct values High cardinality
Yearly bonus + stocks in EUR has a high cardinality: 168 distinct values High cardinality
Annual bonus+stocks one year ago. Only answer if staying in same country has a high cardinality: 131 distinct values High cardinality
Company type has a high cardinality: 101 distinct values High cardinality
Have you received additional monetary support from your employer due to Work From Home? If yes, how much in 2020 in EUR has a high cardinality: 59 distinct values High cardinality
Zeitstempel has a high cardinality: 991 distinct values High cardinality
Position (without seniority) has a high cardinality: 51 distinct values High cardinality
Company name has a high cardinality: 220 distinct values High cardinality
Company business sector has a high cardinality: 52 distinct values High cardinality
Position has a high cardinality: 397 distinct values High cardinality
Age is highly correlated with Years of experienceHigh correlation
Yearly brutto salary (without bonus and stocks) in EUR is highly correlated with Annual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same countryHigh correlation
Annual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same country is highly correlated with Yearly brutto salary (without bonus and stocks) in EURHigh correlation
Years of experience is highly correlated with AgeHigh correlation
Yearly brutto salary (without bonus and stocks) is highly correlated with Yearly bonus and 1 other fieldsHigh correlation
Yearly bonus is highly correlated with Yearly brutto salary (without bonus and stocks) and 3 other fieldsHigh correlation
Yearly stocks is highly correlated with Yearly bonus and 1 other fieldsHigh correlation
Yearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same country is highly correlated with Yearly brutto salary (without bonus and stocks)High correlation
Yearly bonus one year ago. Only answer if staying in same country is highly correlated with Yearly bonus and 1 other fieldsHigh correlation
Yearly stocks one year ago. Only answer if staying in same country is highly correlated with Yearly bonus and 2 other fieldsHigh correlation
Current Salary is highly correlated with Salary one year ago and 1 other fieldsHigh correlation
Salary one year ago is highly correlated with Current Salary and 1 other fieldsHigh correlation
Salary two years ago is highly correlated with Current Salary and 1 other fieldsHigh correlation
Age is highly correlated with Years of experienceHigh correlation
Yearly brutto salary (without bonus and stocks) in EUR is highly correlated with Annual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same countryHigh correlation
Annual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same country is highly correlated with Yearly brutto salary (without bonus and stocks) in EURHigh correlation
Years of experience is highly correlated with Age and 3 other fieldsHigh correlation
Yearly brutto salary (without bonus and stocks) is highly correlated with Yearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same countryHigh correlation
Yearly bonus is highly correlated with Yearly stocks and 2 other fieldsHigh correlation
Yearly stocks is highly correlated with Yearly bonus and 2 other fieldsHigh correlation
Yearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same country is highly correlated with Years of experience and 1 other fieldsHigh correlation
Yearly bonus one year ago. Only answer if staying in same country is highly correlated with Yearly bonus and 2 other fieldsHigh correlation
Yearly stocks one year ago. Only answer if staying in same country is highly correlated with Yearly bonus and 2 other fieldsHigh correlation
Current Salary is highly correlated with Salary one year ago and 1 other fieldsHigh correlation
Salary one year ago is highly correlated with Years of experience and 2 other fieldsHigh correlation
Salary two years ago is highly correlated with Years of experience and 2 other fieldsHigh correlation
Yearly brutto salary (without bonus and stocks) in EUR is highly correlated with Annual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same countryHigh correlation
Annual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same country is highly correlated with Yearly brutto salary (without bonus and stocks) in EURHigh correlation
Yearly brutto salary (without bonus and stocks) is highly correlated with Yearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same countryHigh correlation
Yearly bonus is highly correlated with Yearly stocks and 1 other fieldsHigh correlation
Yearly stocks is highly correlated with Yearly bonus and 2 other fieldsHigh correlation
Yearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same country is highly correlated with Yearly brutto salary (without bonus and stocks)High correlation
Yearly bonus one year ago. Only answer if staying in same country is highly correlated with Yearly bonus and 2 other fieldsHigh correlation
Yearly stocks one year ago. Only answer if staying in same country is highly correlated with Yearly stocks and 1 other fieldsHigh correlation
Current Salary is highly correlated with Salary one year ago and 1 other fieldsHigh correlation
Salary one year ago is highly correlated with Current Salary and 1 other fieldsHigh correlation
Salary two years ago is highly correlated with Current Salary and 1 other fieldsHigh correlation
Yearly brutto salary (without bonus and stocks) is highly correlated with Position (without seniority) and 5 other fieldsHigh correlation
Position (without seniority) is highly correlated with Yearly brutto salary (without bonus and stocks) and 5 other fieldsHigh correlation
Employment status is highly correlated with Seniority level and 3 other fieldsHigh correlation
Yearly stocks one year ago. Only answer if staying in same country is highly correlated with Yearly brutto salary (without bonus and stocks) and 5 other fieldsHigh correlation
Age is highly correlated with Years of experience and 2 other fieldsHigh correlation
Years of experience is highly correlated with Age and 3 other fieldsHigh correlation
Company business sector is highly correlated with Position (without seniority) and 1 other fieldsHigh correlation
Your level is highly correlated with Years of experience and 1 other fieldsHigh correlation
Have you lost your job due to the coronavirus outbreak? is highly correlated with Years of experience in Germany and 1 other fieldsHigh correlation
Yearly stocks is highly correlated with Yearly brutto salary (without bonus and stocks) and 3 other fieldsHigh correlation
Seniority level is highly correlated with Yearly brutto salary (without bonus and stocks) and 6 other fieldsHigh correlation
Years of experience in Germany is highly correlated with Employment status and 5 other fieldsHigh correlation
Salary one year ago is highly correlated with Salary two years ago and 1 other fieldsHigh correlation
Total years of experience is highly correlated with Employment status and 4 other fieldsHigh correlation
Company size is highly correlated with Сontract durationHigh correlation
Number of home office days per month is highly correlated with Yearly stocks one year ago. Only answer if staying in same country and 2 other fieldsHigh correlation
Have you received additional monetary support from your employer due to Work From Home? If yes, how much in 2020 in EUR is highly correlated with Employment status and 3 other fieldsHigh correlation
Сontract duration is highly correlated with Company sizeHigh correlation
Salary two years ago is highly correlated with Your level and 2 other fieldsHigh correlation
Main language at work is highly correlated with Position (without seniority)High correlation
Yearly bonus one year ago. Only answer if staying in same country is highly correlated with Yearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same country and 1 other fieldsHigh correlation
Yearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same country is highly correlated with Yearly brutto salary (without bonus and stocks) and 2 other fieldsHigh correlation
Yearly bonus is highly correlated with Yearly brutto salary (without bonus and stocks) and 3 other fieldsHigh correlation
Current Salary is highly correlated with Years of experience and 2 other fieldsHigh correlation
Timestamp has 991 (32.9%) missing values Missing
Age has 229 (7.6%) missing values Missing
Position has 1762 (58.6%) missing values Missing
Total years of experience has 1772 (58.9%) missing values Missing
Years of experience in Germany has 1788 (59.4%) missing values Missing
Seniority level has 792 (26.3%) missing values Missing
Your main technology / programming language has 906 (30.1%) missing values Missing
Other technologies/programming languages you use often has 1913 (63.6%) missing values Missing
Yearly brutto salary (without bonus and stocks) in EUR has 1756 (58.4%) missing values Missing
Yearly bonus + stocks in EUR has 2180 (72.4%) missing values Missing
Annual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same country has 2124 (70.6%) missing values Missing
Annual bonus+stocks one year ago. Only answer if staying in same country has 2395 (79.6%) missing values Missing
Number of vacation days has 893 (29.7%) missing values Missing
Employment status has 1773 (58.9%) missing values Missing
Сontract duration has 823 (27.4%) missing values Missing
Main language at work has 36 (1.2%) missing values Missing
Company size has 47 (1.6%) missing values Missing
Company type has 91 (3.0%) missing values Missing
Have you lost your job due to the coronavirus outbreak? has 1776 (59.0%) missing values Missing
Have you been forced to have a shorter working week (Kurzarbeit)? If yes, how many hours per week has 2636 (87.6%) missing values Missing
Have you received additional monetary support from your employer due to Work From Home? If yes, how much in 2020 in EUR has 2547 (84.6%) missing values Missing
Zeitstempel has 2018 (67.1%) missing values Missing
Position (without seniority) has 2019 (67.1%) missing values Missing
Years of experience has 1286 (42.7%) missing values Missing
Yearly brutto salary (without bonus and stocks) has 2019 (67.1%) missing values Missing
Yearly bonus has 2479 (82.4%) missing values Missing
Yearly stocks has 2806 (93.3%) missing values Missing
Yearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same country has 2406 (80.0%) missing values Missing
Yearly bonus one year ago. Only answer if staying in same country has 2752 (91.5%) missing values Missing
Yearly stocks one year ago. Only answer if staying in same country has 2870 (95.4%) missing values Missing
Number of home office days per month has 2370 (78.8%) missing values Missing
Company name has 2752 (91.5%) missing values Missing
Company business sector has 2163 (71.9%) missing values Missing
0 has 3009 (100.0%) missing values Missing
Position has 2272 (75.5%) missing values Missing
Your level has 2266 (75.3%) missing values Missing
Current Salary has 2259 (75.1%) missing values Missing
Salary one year ago has 2413 (80.2%) missing values Missing
Salary two years ago has 2546 (84.6%) missing values Missing
Are you getting any Stock Options? has 2267 (75.3%) missing values Missing
Yearly brutto salary (without bonus and stocks) in EUR is highly skewed (γ1 = 35.39641533) Skewed
Annual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same country is highly skewed (γ1 = 29.74879226) Skewed
Timestamp is uniformly distributed Uniform
Zeitstempel is uniformly distributed Uniform
Company name is uniformly distributed Uniform
Number of vacation days is an unsupported type, check if it needs cleaning or further analysis Unsupported
0 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Have you been forced to have a shorter working week (Kurzarbeit)? If yes, how many hours per week has 197 (6.5%) zeros Zeros
Yearly bonus has 123 (4.1%) zeros Zeros
Yearly stocks has 31 (1.0%) zeros Zeros
Yearly stocks one year ago. Only answer if staying in same country has 68 (2.3%) zeros Zeros
Number of home office days per month has 101 (3.4%) zeros Zeros

Reproduction

Analysis started2021-06-26 16:22:28.073042
Analysis finished2021-06-26 16:23:18.898725
Duration50.83 seconds
Software versionpandas-profiling v3.0.0
Download configurationconfig.json

Variables

df_index
Real number (ℝ≥0)

Distinct1253
Distinct (%)41.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean520.8218677
Minimum0
Maximum1252
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum0
5-th percentile50
Q1250
median501
Q3752
95-th percentile1101.6
Maximum1252
Range1252
Interquartile range (IQR)502

Descriptive statistics

Standard deviation321.8604404
Coefficient of variation (CV)0.61798565
Kurtosis-0.8368318496
Mean520.8218677
Median Absolute Deviation (MAD)251
Skewness0.2923427676
Sum1567153
Variance103594.1431
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
03
 
0.1%
733
 
0.1%
953
 
0.1%
933
 
0.1%
913
 
0.1%
893
 
0.1%
873
 
0.1%
853
 
0.1%
833
 
0.1%
813
 
0.1%
Other values (1243)2979
99.0%
ValueCountFrequency (%)
03
0.1%
13
0.1%
23
0.1%
33
0.1%
43
0.1%
53
0.1%
63
0.1%
73
0.1%
83
0.1%
93
0.1%
ValueCountFrequency (%)
12521
< 0.1%
12511
< 0.1%
12501
< 0.1%
12491
< 0.1%
12481
< 0.1%
12471
< 0.1%
12461
< 0.1%
12451
< 0.1%
12441
< 0.1%
12431
< 0.1%

Timestamp
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct2009
Distinct (%)99.6%
Missing991
Missing (%)32.9%
Memory size23.6 KiB
25/11/2020 18:28:01
 
2
14/12/2018 12:53:47
 
2
24/11/2020 14:07:23
 
2
14/12/2018 13:43:50
 
2
25/11/2020 08:47:37
 
2
Other values (2004)
2008 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters38342
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2000 ?
Unique (%)99.1%

Sample

1st row24/11/2020 11:14:15
2nd row24/11/2020 11:14:16
3rd row24/11/2020 11:14:21
4th row24/11/2020 11:15:24
5th row24/11/2020 11:15:46

Common Values

ValueCountFrequency (%)
25/11/2020 18:28:012
 
0.1%
14/12/2018 12:53:472
 
0.1%
24/11/2020 14:07:232
 
0.1%
14/12/2018 13:43:502
 
0.1%
25/11/2020 08:47:372
 
0.1%
24/11/2020 13:55:192
 
0.1%
24/11/2020 15:07:352
 
0.1%
14/12/2018 14:35:192
 
0.1%
14/12/2018 13:44:092
 
0.1%
24/11/2020 15:04:231
 
< 0.1%
Other values (1999)1999
66.4%
(Missing)991
32.9%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
24/11/2020467
 
11.6%
25/11/2020253
 
6.3%
14/12/2018252
 
6.2%
15/12/2018121
 
3.0%
26/11/202091
 
2.3%
30/11/202086
 
2.1%
18/12/201872
 
1.8%
27/11/202072
 
1.8%
17/12/201856
 
1.4%
19/12/201847
 
1.2%
Other values (2086)2519
62.4%

Most occurring characters

ValueCountFrequency (%)
17417
19.3%
27032
18.3%
05208
13.6%
/4036
10.5%
:4036
10.5%
2018
 
5.3%
41993
 
5.2%
51638
 
4.3%
31481
 
3.9%
81421
 
3.7%
Other values (3)2062
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number28252
73.7%
Other Punctuation8072
 
21.1%
Space Separator2018
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
17417
26.3%
27032
24.9%
05208
18.4%
41993
 
7.1%
51638
 
5.8%
31481
 
5.2%
81421
 
5.0%
7710
 
2.5%
9678
 
2.4%
6674
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/4036
50.0%
:4036
50.0%
Space Separator
ValueCountFrequency (%)
2018
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common38342
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
17417
19.3%
27032
18.3%
05208
13.6%
/4036
10.5%
:4036
10.5%
2018
 
5.3%
41993
 
5.2%
51638
 
4.3%
31481
 
3.9%
81421
 
3.7%
Other values (3)2062
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII38342
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17417
19.3%
27032
18.3%
05208
13.6%
/4036
10.5%
:4036
10.5%
2018
 
5.3%
41993
 
5.2%
51638
 
4.3%
31481
 
3.9%
81421
 
3.7%
Other values (3)2062
 
5.4%

Age
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct41
Distinct (%)1.5%
Missing229
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean32.40107914
Minimum20
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum20
5-th percentile25
Q129
median32
Q335
95-th percentile42
Maximum69
Range49
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.406931059
Coefficient of variation (CV)0.1668750302
Kurtosis2.808929424
Mean32.40107914
Median Absolute Deviation (MAD)3
Skewness1.045417164
Sum90075
Variance29.23490348
MonotonicityNot monotonic
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
30274
 
9.1%
33231
 
7.7%
32230
 
7.6%
31218
 
7.2%
29187
 
6.2%
28181
 
6.0%
35181
 
6.0%
34171
 
5.7%
27136
 
4.5%
36126
 
4.2%
Other values (31)845
28.1%
(Missing)229
 
7.6%
ValueCountFrequency (%)
202
 
0.1%
216
 
0.2%
2218
 
0.6%
2325
 
0.8%
2460
 
2.0%
2595
3.2%
26119
4.0%
27136
4.5%
28181
6.0%
29187
6.2%
ValueCountFrequency (%)
691
 
< 0.1%
661
 
< 0.1%
651
 
< 0.1%
601
 
< 0.1%
591
 
< 0.1%
562
 
0.1%
543
0.1%
531
 
< 0.1%
525
0.2%
512
 
0.1%

Gender
Categorical

Distinct5
Distinct (%)0.2%
Missing24
Missing (%)0.8%
Memory size23.6 KiB
Male
1887 
M
646 
Female
345 
F
 
105
Diverse
 
2

Length

Max length7
Median length4
Mean length3.47839196
Min length1

Characters and Unicode

Total characters10383
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMale
2nd rowMale
3rd rowMale
4th rowMale
5th rowMale

Common Values

ValueCountFrequency (%)
Male1887
62.7%
M646
 
21.5%
Female345
 
11.5%
F105
 
3.5%
Diverse2
 
0.1%
(Missing)24
 
0.8%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
male1887
63.2%
m646
 
21.6%
female345
 
11.6%
f105
 
3.5%
diverse2
 
0.1%

Most occurring characters

ValueCountFrequency (%)
e2581
24.9%
M2533
24.4%
a2232
21.5%
l2232
21.5%
F450
 
4.3%
m345
 
3.3%
D2
 
< 0.1%
i2
 
< 0.1%
v2
 
< 0.1%
r2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7398
71.3%
Uppercase Letter2985
28.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2581
34.9%
a2232
30.2%
l2232
30.2%
m345
 
4.7%
i2
 
< 0.1%
v2
 
< 0.1%
r2
 
< 0.1%
s2
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
M2533
84.9%
F450
 
15.1%
D2
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin10383
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2581
24.9%
M2533
24.4%
a2232
21.5%
l2232
21.5%
F450
 
4.3%
m345
 
3.3%
D2
 
< 0.1%
i2
 
< 0.1%
v2
 
< 0.1%
r2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII10383
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e2581
24.9%
M2533
24.4%
a2232
21.5%
l2232
21.5%
F450
 
4.3%
m345
 
3.3%
D2
 
< 0.1%
i2
 
< 0.1%
v2
 
< 0.1%
r2
 
< 0.1%

City
Categorical

HIGH CARDINALITY

Distinct183
Distinct (%)6.1%
Missing29
Missing (%)1.0%
Memory size23.6 KiB
Berlin
1402 
Munich
476 
München
249 
Frankfurt
 
127
Amsterdam
 
104
Other values (178)
622 

Length

Max length21
Median length6
Mean length6.682214765
Min length2

Characters and Unicode

Total characters19913
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)3.6%

Sample

1st rowMunich
2nd rowBerlin
3rd rowBerlin
4th rowBerlin
5th rowBerlin

Common Values

ValueCountFrequency (%)
Berlin1402
46.6%
Munich476
 
15.8%
München249
 
8.3%
Frankfurt127
 
4.2%
Amsterdam104
 
3.5%
Hamburg90
 
3.0%
Stuttgart56
 
1.9%
Cologne36
 
1.2%
Köln21
 
0.7%
Moscow19
 
0.6%
Other values (173)400
 
13.3%
(Missing)29
 
1.0%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
berlin1402
46.7%
munich476
 
15.9%
münchen249
 
8.3%
frankfurt127
 
4.2%
amsterdam106
 
3.5%
hamburg90
 
3.0%
stuttgart66
 
2.2%
cologne36
 
1.2%
düsseldorf21
 
0.7%
köln21
 
0.7%
Other values (166)408
 
13.6%

Most occurring characters

ValueCountFrequency (%)
n2811
14.1%
r2187
11.0%
e2099
10.5%
i2048
10.3%
l1619
 
8.1%
B1435
 
7.2%
u879
 
4.4%
h800
 
4.0%
c793
 
4.0%
M767
 
3.9%
Other values (45)4475
22.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter16837
84.6%
Uppercase Letter3000
 
15.1%
Space Separator60
 
0.3%
Dash Punctuation7
 
< 0.1%
Other Punctuation7
 
< 0.1%
Open Punctuation1
 
< 0.1%
Close Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n2811
16.7%
r2187
13.0%
e2099
12.5%
i2048
12.2%
l1619
9.6%
u879
 
5.2%
h800
 
4.8%
c793
 
4.7%
a595
 
3.5%
t580
 
3.4%
Other values (17)2426
14.4%
Uppercase Letter
ValueCountFrequency (%)
B1435
47.8%
M767
25.6%
F133
 
4.4%
A116
 
3.9%
H115
 
3.8%
S97
 
3.2%
K67
 
2.2%
D48
 
1.6%
C43
 
1.4%
L35
 
1.2%
Other values (13)144
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
-7
100.0%
Space Separator
ValueCountFrequency (%)
60
100.0%
Other Punctuation
ValueCountFrequency (%)
,7
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin19837
99.6%
Common76
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n2811
14.2%
r2187
11.0%
e2099
10.6%
i2048
10.3%
l1619
 
8.2%
B1435
 
7.2%
u879
 
4.4%
h800
 
4.0%
c793
 
4.0%
M767
 
3.9%
Other values (40)4399
22.2%
Common
ValueCountFrequency (%)
60
78.9%
-7
 
9.2%
,7
 
9.2%
(1
 
1.3%
)1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII19602
98.4%
Latin 1 Sup310
 
1.6%
Latin Ext A1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n2811
14.3%
r2187
11.2%
e2099
10.7%
i2048
10.4%
l1619
 
8.3%
B1435
 
7.3%
u879
 
4.5%
h800
 
4.1%
c793
 
4.0%
M767
 
3.9%
Other values (42)4164
21.2%
Latin 1 Sup
ValueCountFrequency (%)
ü288
92.9%
ö22
 
7.1%
Latin Ext A
ValueCountFrequency (%)
ń1
100.0%

Position
Categorical

HIGH CARDINALITY
MISSING

Distinct148
Distinct (%)11.9%
Missing1762
Missing (%)58.6%
Memory size23.6 KiB
Software Engineer
387 
Backend Developer
174 
Data Scientist
110 
Frontend Developer
89 
QA Engineer
71 
Other values (143)
416 

Length

Max length44
Median length17
Mean length15.3648757
Min length3

Characters and Unicode

Total characters19160
Distinct characters60
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)9.5%

Sample

1st rowSoftware Engineer
2nd rowBackend Developer
3rd rowSoftware Engineer
4th rowFrontend Developer
5th rowBackend Developer

Common Values

ValueCountFrequency (%)
Software Engineer387
 
12.9%
Backend Developer174
 
5.8%
Data Scientist110
 
3.7%
Frontend Developer89
 
3.0%
QA Engineer71
 
2.4%
DevOps57
 
1.9%
Mobile Developer53
 
1.8%
ML Engineer42
 
1.4%
Product Manager39
 
1.3%
Data Engineer25
 
0.8%
Other values (138)200
 
6.6%
(Missing)1762
58.6%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
engineer551
22.4%
software399
16.2%
developer330
13.4%
backend174
 
7.1%
data156
 
6.3%
scientist110
 
4.5%
frontend89
 
3.6%
qa75
 
3.1%
manager74
 
3.0%
devops58
 
2.4%
Other values (115)443
18.0%

Most occurring characters

ValueCountFrequency (%)
e3273
17.1%
n1812
 
9.5%
r1618
 
8.4%
1232
 
6.4%
a1177
 
6.1%
t1072
 
5.6%
o992
 
5.2%
i958
 
5.0%
g693
 
3.6%
E570
 
3.0%
Other values (50)5763
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter15166
79.2%
Uppercase Letter2693
 
14.1%
Space Separator1232
 
6.4%
Other Punctuation29
 
0.2%
Open Punctuation18
 
0.1%
Close Punctuation18
 
0.1%
Math Symbol2
 
< 0.1%
Dash Punctuation2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3273
21.6%
n1812
11.9%
r1618
10.7%
a1177
 
7.8%
t1072
 
7.1%
o992
 
6.5%
i958
 
6.3%
g693
 
4.6%
l461
 
3.0%
f411
 
2.7%
Other values (18)2699
17.8%
Uppercase Letter
ValueCountFrequency (%)
E570
21.2%
D567
21.1%
S548
20.3%
B190
 
7.1%
M169
 
6.3%
A121
 
4.5%
F98
 
3.6%
Q75
 
2.8%
O68
 
2.5%
P59
 
2.2%
Other values (13)228
 
8.5%
Other Punctuation
ValueCountFrequency (%)
/24
82.8%
,3
 
10.3%
&1
 
3.4%
.1
 
3.4%
Space Separator
ValueCountFrequency (%)
1232
100.0%
Open Punctuation
ValueCountFrequency (%)
(18
100.0%
Close Punctuation
ValueCountFrequency (%)
)18
100.0%
Math Symbol
ValueCountFrequency (%)
+2
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin17854
93.2%
Common1301
 
6.8%
Cyrillic5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3273
18.3%
n1812
 
10.1%
r1618
 
9.1%
a1177
 
6.6%
t1072
 
6.0%
o992
 
5.6%
i958
 
5.4%
g693
 
3.9%
E570
 
3.2%
D567
 
3.2%
Other values (37)5122
28.7%
Common
ValueCountFrequency (%)
1232
94.7%
/24
 
1.8%
(18
 
1.4%
)18
 
1.4%
,3
 
0.2%
+2
 
0.2%
-2
 
0.2%
&1
 
0.1%
.1
 
0.1%
Cyrillic
ValueCountFrequency (%)
и2
40.0%
н1
20.0%
у1
20.0%
л1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII19155
> 99.9%
Cyrillic5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e3273
17.1%
n1812
 
9.5%
r1618
 
8.4%
1232
 
6.4%
a1177
 
6.1%
t1072
 
5.6%
o992
 
5.2%
i958
 
5.0%
g693
 
3.6%
E570
 
3.0%
Other values (46)5758
30.1%
Cyrillic
ValueCountFrequency (%)
и2
40.0%
н1
20.0%
у1
20.0%
л1
20.0%

Total years of experience
Categorical

HIGH CORRELATION
MISSING

Distinct48
Distinct (%)3.9%
Missing1772
Missing (%)58.9%
Memory size23.6 KiB
10
138 
5
136 
6
99 
8
92 
7
84 
Other values (43)
688 

Length

Max length51
Median length1
Mean length1.528698464
Min length1

Characters and Unicode

Total characters1891
Distinct characters39
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)1.2%

Sample

1st row5
2nd row7
3rd row12
4th row4
5th row17

Common Values

ValueCountFrequency (%)
10138
 
4.6%
5136
 
4.5%
699
 
3.3%
892
 
3.1%
784
 
2.8%
480
 
2.7%
1267
 
2.2%
366
 
2.2%
1563
 
2.1%
960
 
2.0%
Other values (38)352
 
11.7%
(Missing)1772
58.9%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
10138
 
11.0%
5136
 
10.8%
6100
 
7.9%
893
 
7.4%
784
 
6.7%
480
 
6.3%
1267
 
5.3%
366
 
5.2%
1564
 
5.1%
960
 
4.8%
Other values (51)372
29.5%

Most occurring characters

ValueCountFrequency (%)
1532
28.1%
5224
11.8%
2185
 
9.8%
0179
 
9.5%
4123
 
6.5%
6122
 
6.5%
3118
 
6.2%
8113
 
6.0%
799
 
5.2%
968
 
3.6%
Other values (29)128
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1763
93.2%
Lowercase Letter74
 
3.9%
Space Separator23
 
1.2%
Other Punctuation21
 
1.1%
Uppercase Letter6
 
0.3%
Open Punctuation2
 
0.1%
Close Punctuation2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a12
16.2%
t11
14.9%
s10
13.5%
e8
10.8%
n7
9.5%
i6
8.1%
r3
 
4.1%
o3
 
4.1%
l3
 
4.1%
h2
 
2.7%
Other values (7)9
12.2%
Decimal Number
ValueCountFrequency (%)
1532
30.2%
5224
12.7%
2185
 
10.5%
0179
 
10.2%
4123
 
7.0%
6122
 
6.9%
3118
 
6.7%
8113
 
6.4%
799
 
5.6%
968
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
Q1
16.7%
A1
16.7%
E1
16.7%
C1
16.7%
T1
16.7%
O1
16.7%
Other Punctuation
ValueCountFrequency (%)
.15
71.4%
,5
 
23.8%
/1
 
4.8%
Space Separator
ValueCountFrequency (%)
23
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1811
95.8%
Latin80
 
4.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a12
15.0%
t11
13.8%
s10
12.5%
e8
10.0%
n7
8.8%
i6
 
7.5%
r3
 
3.8%
o3
 
3.8%
l3
 
3.8%
h2
 
2.5%
Other values (13)15
18.8%
Common
ValueCountFrequency (%)
1532
29.4%
5224
12.4%
2185
 
10.2%
0179
 
9.9%
4123
 
6.8%
6122
 
6.7%
3118
 
6.5%
8113
 
6.2%
799
 
5.5%
968
 
3.8%
Other values (6)48
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII1891
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1532
28.1%
5224
11.8%
2185
 
9.8%
0179
 
9.5%
4123
 
6.5%
6122
 
6.5%
3118
 
6.2%
8113
 
6.0%
799
 
5.2%
968
 
3.6%
Other values (29)128
 
6.8%

Years of experience in Germany
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct53
Distinct (%)4.3%
Missing1788
Missing (%)59.4%
Memory size23.6 KiB
2
195 
1
189 
3
155 
5
142 
4
122 
Other values (48)
418 

Length

Max length51
Median length1
Mean length1.305487305
Min length1

Characters and Unicode

Total characters1594
Distinct characters39
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)2.0%

Sample

1st row3
2nd row4
3rd row6
4th row1
5th row6

Common Values

ValueCountFrequency (%)
2195
 
6.5%
1189
 
6.3%
3155
 
5.2%
5142
 
4.7%
4122
 
4.1%
099
 
3.3%
670
 
2.3%
737
 
1.2%
1029
 
1.0%
1.524
 
0.8%
Other values (43)159
 
5.3%
(Missing)1788
59.4%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
2195
15.7%
1191
15.4%
3157
12.6%
5142
11.4%
4124
10.0%
0100
8.0%
671
 
5.7%
737
 
3.0%
1029
 
2.3%
1.524
 
1.9%
Other values (51)173
13.9%

Most occurring characters

ValueCountFrequency (%)
1300
18.8%
2232
14.6%
5225
14.1%
3176
11.0%
0165
10.4%
4132
8.3%
674
 
4.6%
.65
 
4.1%
739
 
2.4%
923
 
1.4%
Other values (29)163
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1386
87.0%
Lowercase Letter87
 
5.5%
Other Punctuation84
 
5.3%
Space Separator22
 
1.4%
Open Punctuation4
 
0.3%
Close Punctuation4
 
0.3%
Uppercase Letter3
 
0.2%
Math Symbol2
 
0.1%
Other Number1
 
0.1%
Dash Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n12
13.8%
a12
13.8%
t11
12.6%
s9
10.3%
i8
9.2%
e6
 
6.9%
l4
 
4.6%
o4
 
4.6%
r3
 
3.4%
d3
 
3.4%
Other values (8)15
17.2%
Decimal Number
ValueCountFrequency (%)
1300
21.6%
2232
16.7%
5225
16.2%
3176
12.7%
0165
11.9%
4132
9.5%
674
 
5.3%
739
 
2.8%
923
 
1.7%
820
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
S1
33.3%
G1
33.3%
P1
33.3%
Other Punctuation
ValueCountFrequency (%)
.65
77.4%
,19
 
22.6%
Math Symbol
ValueCountFrequency (%)
<2
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Open Punctuation
ValueCountFrequency (%)
(4
100.0%
Close Punctuation
ValueCountFrequency (%)
)4
100.0%
Other Number
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1504
94.4%
Latin90
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n12
13.3%
a12
13.3%
t11
12.2%
s9
10.0%
i8
8.9%
e6
 
6.7%
l4
 
4.4%
o4
 
4.4%
r3
 
3.3%
d3
 
3.3%
Other values (11)18
20.0%
Common
ValueCountFrequency (%)
1300
19.9%
2232
15.4%
5225
15.0%
3176
11.7%
0165
11.0%
4132
8.8%
674
 
4.9%
.65
 
4.3%
739
 
2.6%
923
 
1.5%
Other values (8)73
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII1593
99.9%
None1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1300
18.8%
2232
14.6%
5225
14.1%
3176
11.0%
0165
10.4%
4132
8.3%
674
 
4.6%
.65
 
4.1%
739
 
2.4%
923
 
1.4%
Other values (28)162
10.2%
None
ValueCountFrequency (%)
1
100.0%

Seniority level
Categorical

HIGH CORRELATION
MISSING

Distinct24
Distinct (%)1.1%
Missing792
Missing (%)26.3%
Memory size23.6 KiB
Senior
1152 
Middle
638 
Lead
201 
Junior
152 
Head
 
50
Other values (19)
 
24

Length

Max length41
Median length6
Mean length5.821831304
Min length2

Characters and Unicode

Total characters12907
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)0.8%

Sample

1st rowSenior
2nd rowSenior
3rd rowLead
4th rowJunior
5th rowSenior

Common Values

ValueCountFrequency (%)
Senior1152
38.3%
Middle638
21.2%
Lead201
 
6.7%
Junior152
 
5.1%
Head50
 
1.7%
Principal6
 
0.2%
Student1
 
< 0.1%
C-level executive manager1
 
< 0.1%
Intern1
 
< 0.1%
No level 1
 
< 0.1%
Other values (14)14
 
0.5%
(Missing)792
26.3%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
senior1152
51.6%
middle638
28.6%
lead201
 
9.0%
junior152
 
6.8%
head50
 
2.2%
principal6
 
0.3%
no4
 
0.2%
level3
 
0.1%
manager3
 
0.1%
student3
 
0.1%
Other values (20)22
 
1.0%

Most occurring characters

ValueCountFrequency (%)
e2075
16.1%
i1961
15.2%
d1532
11.9%
n1327
10.3%
r1325
10.3%
o1312
10.2%
S1155
8.9%
l655
 
5.1%
M640
 
5.0%
a266
 
2.1%
Other values (30)659
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter10664
82.6%
Uppercase Letter2221
 
17.2%
Space Separator19
 
0.1%
Dash Punctuation2
 
< 0.1%
Other Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2075
19.5%
i1961
18.4%
d1532
14.4%
n1327
12.4%
r1325
12.4%
o1312
12.3%
l655
 
6.1%
a266
 
2.5%
u156
 
1.5%
t14
 
0.1%
Other values (11)41
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
S1155
52.0%
M640
28.8%
L202
 
9.1%
J152
 
6.8%
H50
 
2.3%
P7
 
0.3%
C4
 
0.2%
N2
 
0.1%
W2
 
0.1%
V1
 
< 0.1%
Other values (6)6
 
0.3%
Space Separator
ValueCountFrequency (%)
19
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin12885
99.8%
Common22
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2075
16.1%
i1961
15.2%
d1532
11.9%
n1327
10.3%
r1325
10.3%
o1312
10.2%
S1155
9.0%
l655
 
5.1%
M640
 
5.0%
a266
 
2.1%
Other values (27)637
 
4.9%
Common
ValueCountFrequency (%)
19
86.4%
-2
 
9.1%
,1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII12907
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e2075
16.1%
i1961
15.2%
d1532
11.9%
n1327
10.3%
r1325
10.3%
o1312
10.2%
S1155
8.9%
l655
 
5.1%
M640
 
5.0%
a266
 
2.1%
Other values (30)659
 
5.1%

Your main technology / programming language
Categorical

HIGH CARDINALITY
MISSING

Distinct274
Distinct (%)13.0%
Missing906
Missing (%)30.1%
Memory size23.6 KiB
Python
369 
Java
365 
Not Relevant
119 
Javascript / Typescript
113 
PHP
108 
Other values (269)
1029 

Length

Max length60
Median length5
Mean length7.038991916
Min length1

Characters and Unicode

Total characters14803
Distinct characters70
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)9.4%

Sample

1st rowTypeScript
2nd rowRuby
3rd rowJavascript / Typescript
4th rowJavascript
5th rowC# .NET

Common Values

ValueCountFrequency (%)
Python369
12.3%
Java365
12.1%
Not Relevant119
 
4.0%
Javascript / Typescript113
 
3.8%
PHP108
 
3.6%
Kotlin56
 
1.9%
.NET54
 
1.8%
C/C++46
 
1.5%
Swift44
 
1.5%
AWS43
 
1.4%
Other values (264)786
26.1%
(Missing)906
30.1%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
python432
16.3%
java391
14.8%
javascript203
 
7.7%
typescript152
 
5.7%
133
 
5.0%
php126
 
4.8%
relevant119
 
4.5%
not119
 
4.5%
c97
 
3.7%
net70
 
2.6%
Other values (198)805
30.4%

Most occurring characters

ValueCountFrequency (%)
a1533
 
10.4%
t1283
 
8.7%
o802
 
5.4%
n739
 
5.0%
v738
 
5.0%
P692
 
4.7%
y655
 
4.4%
e622
 
4.2%
J615
 
4.2%
p608
 
4.1%
Other values (60)6516
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter10330
69.8%
Uppercase Letter3235
 
21.9%
Space Separator592
 
4.0%
Other Punctuation429
 
2.9%
Math Symbol195
 
1.3%
Dash Punctuation11
 
0.1%
Decimal Number5
 
< 0.1%
Open Punctuation3
 
< 0.1%
Close Punctuation3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a1533
14.8%
t1283
12.4%
o802
 
7.8%
n739
 
7.2%
v738
 
7.1%
y655
 
6.3%
e622
 
6.0%
p608
 
5.9%
i580
 
5.6%
r503
 
4.9%
Other values (18)2267
21.9%
Uppercase Letter
ValueCountFrequency (%)
P692
21.4%
J615
19.0%
S329
10.2%
T228
 
7.0%
R219
 
6.8%
C218
 
6.7%
N199
 
6.2%
A135
 
4.2%
H122
 
3.8%
K84
 
2.6%
Other values (17)394
12.2%
Other Punctuation
ValueCountFrequency (%)
/206
48.0%
,102
23.8%
.78
 
18.2%
#39
 
9.1%
&2
 
0.5%
*1
 
0.2%
:1
 
0.2%
Decimal Number
ValueCountFrequency (%)
83
60.0%
61
 
20.0%
31
 
20.0%
Space Separator
ValueCountFrequency (%)
592
100.0%
Math Symbol
ValueCountFrequency (%)
+195
100.0%
Dash Punctuation
ValueCountFrequency (%)
-11
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin13560
91.6%
Common1238
 
8.4%
Cyrillic5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a1533
 
11.3%
t1283
 
9.5%
o802
 
5.9%
n739
 
5.4%
v738
 
5.4%
P692
 
5.1%
y655
 
4.8%
e622
 
4.6%
J615
 
4.5%
p608
 
4.5%
Other values (41)5273
38.9%
Common
ValueCountFrequency (%)
592
47.8%
/206
 
16.6%
+195
 
15.8%
,102
 
8.2%
.78
 
6.3%
#39
 
3.2%
-11
 
0.9%
83
 
0.2%
(3
 
0.2%
)3
 
0.2%
Other values (5)6
 
0.5%
Cyrillic
ValueCountFrequency (%)
ф2
40.0%
С1
20.0%
О1
20.0%
м1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII14798
> 99.9%
Cyrillic5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a1533
 
10.4%
t1283
 
8.7%
o802
 
5.4%
n739
 
5.0%
v738
 
5.0%
P692
 
4.7%
y655
 
4.4%
e622
 
4.2%
J615
 
4.2%
p608
 
4.1%
Other values (56)6511
44.0%
Cyrillic
ValueCountFrequency (%)
ф2
40.0%
С1
20.0%
О1
20.0%
м1
20.0%
Distinct562
Distinct (%)51.3%
Missing1913
Missing (%)63.6%
Memory size23.6 KiB
Javascript / Typescript
 
44
Python
 
37
SQL
 
31
AWS, Docker
 
16
Kotlin
 
15
Other values (557)
953 

Length

Max length121
Median length28
Mean length30.83394161
Min length2

Characters and Unicode

Total characters33794
Distinct characters59
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique407 ?
Unique (%)37.1%

Sample

1st rowKotlin, Javascript / Typescript
2nd rowJavascript / Typescript, Docker
3rd row.NET, SQL, AWS, Docker
4th rowPython, AWS, Google Cloud, Kubernetes, Docker
5th rowJavascript / Typescript

Common Values

ValueCountFrequency (%)
Javascript / Typescript44
 
1.5%
Python37
 
1.2%
SQL31
 
1.0%
AWS, Docker16
 
0.5%
Kotlin15
 
0.5%
C/C++13
 
0.4%
Swift13
 
0.4%
Python, SQL13
 
0.4%
Javascript / Typescript, SQL, AWS, Docker12
 
0.4%
Python, C/C++11
 
0.4%
Other values (552)891
29.6%
(Missing)1913
63.6%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
628
12.1%
docker525
10.2%
sql481
 
9.3%
python409
 
7.9%
aws401
 
7.8%
typescript381
 
7.4%
javascript381
 
7.4%
kubernetes296
 
5.7%
scala230
 
4.4%
java229
 
4.4%
Other values (90)1209
23.4%

Most occurring characters

ValueCountFrequency (%)
4078
 
12.1%
,2651
 
7.8%
e2113
 
6.3%
r1751
 
5.2%
a1735
 
5.1%
t1671
 
4.9%
o1667
 
4.9%
c1544
 
4.6%
S1186
 
3.5%
p1164
 
3.4%
Other values (49)14234
42.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter19167
56.7%
Uppercase Letter6857
 
20.3%
Space Separator4078
 
12.1%
Other Punctuation3476
 
10.3%
Math Symbol211
 
0.6%
Dash Punctuation3
 
< 0.1%
Decimal Number2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2113
11.0%
r1751
 
9.1%
a1735
 
9.1%
t1671
 
8.7%
o1667
 
8.7%
c1544
 
8.1%
p1164
 
6.1%
s1098
 
5.7%
i952
 
5.0%
n850
 
4.4%
Other values (16)4622
24.1%
Uppercase Letter
ValueCountFrequency (%)
S1186
17.3%
P634
9.2%
J612
8.9%
A561
8.2%
D533
7.8%
L487
7.1%
Q486
7.1%
T478
7.0%
K418
 
6.1%
W401
 
5.8%
Other values (13)1061
15.5%
Other Punctuation
ValueCountFrequency (%)
,2651
76.3%
/734
 
21.1%
.88
 
2.5%
#2
 
0.1%
;1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
31
50.0%
21
50.0%
Space Separator
ValueCountFrequency (%)
4078
100.0%
Math Symbol
ValueCountFrequency (%)
+211
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin26024
77.0%
Common7770
 
23.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2113
 
8.1%
r1751
 
6.7%
a1735
 
6.7%
t1671
 
6.4%
o1667
 
6.4%
c1544
 
5.9%
S1186
 
4.6%
p1164
 
4.5%
s1098
 
4.2%
i952
 
3.7%
Other values (39)11143
42.8%
Common
ValueCountFrequency (%)
4078
52.5%
,2651
34.1%
/734
 
9.4%
+211
 
2.7%
.88
 
1.1%
-3
 
< 0.1%
#2
 
< 0.1%
31
 
< 0.1%
21
 
< 0.1%
;1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII33794
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4078
 
12.1%
,2651
 
7.8%
e2113
 
6.3%
r1751
 
5.2%
a1735
 
5.1%
t1671
 
4.9%
o1667
 
4.9%
c1544
 
4.6%
S1186
 
3.5%
p1164
 
3.4%
Other values (49)14234
42.1%

Yearly brutto salary (without bonus and stocks) in EUR
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct201
Distinct (%)16.0%
Missing1756
Missing (%)58.4%
Infinite0
Infinite (%)0.0%
Mean80279042.58
Minimum10001
Maximum1 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum10001
5-th percentile40000
Q158800
median70000
Q380000
95-th percentile110000
Maximum1 × 1011
Range9.999999 × 1010
Interquartile range (IQR)21200

Descriptive statistics

Standard deviation2825061108
Coefficient of variation (CV)35.19051818
Kurtosis1252.93722
Mean80279042.58
Median Absolute Deviation (MAD)10000
Skewness35.39641533
Sum1.005896404 × 1011
Variance7.980970262 × 1018
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000085
 
2.8%
7000083
 
2.8%
6500077
 
2.6%
7500073
 
2.4%
8000066
 
2.2%
9000045
 
1.5%
8500042
 
1.4%
5500035
 
1.2%
7200032
 
1.1%
10000028
 
0.9%
Other values (191)687
 
22.8%
(Missing)1756
58.4%
ValueCountFrequency (%)
100012
0.1%
101641
< 0.1%
110001
< 0.1%
115001
< 0.1%
120002
0.1%
130001
< 0.1%
144001
< 0.1%
147121
< 0.1%
163201
< 0.1%
175001
< 0.1%
ValueCountFrequency (%)
1 × 10111
 
< 0.1%
5000000001
 
< 0.1%
8500001
 
< 0.1%
3000001
 
< 0.1%
2500001
 
< 0.1%
2400001
 
< 0.1%
2000004
0.1%
1800002
0.1%
1720001
 
< 0.1%
1600001
 
< 0.1%

Yearly bonus + stocks in EUR
Categorical

HIGH CARDINALITY
MISSING

Distinct168
Distinct (%)20.3%
Missing2180
Missing (%)72.4%
Memory size23.6 KiB
0
227 
5000
56 
10000
45 
2000
 
36
6000
 
26
Other values (163)
439 

Length

Max length10
Median length4
Mean length3.591073583
Min length1

Characters and Unicode

Total characters2977
Distinct characters30
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)13.6%

Sample

1st row5000
2nd row120000
3rd row5000
4th row101
5th row40000

Common Values

ValueCountFrequency (%)
0227
 
7.5%
500056
 
1.9%
1000045
 
1.5%
200036
 
1.2%
600026
 
0.9%
300023
 
0.8%
100023
 
0.8%
2000021
 
0.7%
400018
 
0.6%
1500016
 
0.5%
Other values (158)338
 
11.2%
(Missing)2180
72.4%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
0227
27.3%
500056
 
6.7%
1000045
 
5.4%
200036
 
4.3%
600026
 
3.1%
300023
 
2.8%
100023
 
2.8%
2000021
 
2.5%
400018
 
2.2%
1500017
 
2.0%
Other values (159)339
40.8%

Most occurring characters

ValueCountFrequency (%)
02044
68.7%
5203
 
6.8%
1195
 
6.6%
2130
 
4.4%
785
 
2.9%
671
 
2.4%
369
 
2.3%
466
 
2.2%
852
 
1.7%
932
 
1.1%
Other values (20)30
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2947
99.0%
Lowercase Letter21
 
0.7%
Other Punctuation2
 
0.1%
Space Separator2
 
0.1%
Dash Punctuation2
 
0.1%
Uppercase Letter2
 
0.1%
Math Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3
14.3%
o2
 
9.5%
n2
 
9.5%
d2
 
9.5%
s2
 
9.5%
b1
 
4.8%
v1
 
4.8%
g1
 
4.8%
l1
 
4.8%
y1
 
4.8%
Other values (5)5
23.8%
Decimal Number
ValueCountFrequency (%)
02044
69.4%
5203
 
6.9%
1195
 
6.6%
2130
 
4.4%
785
 
2.9%
671
 
2.4%
369
 
2.3%
466
 
2.2%
852
 
1.8%
932
 
1.1%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
+1
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2
100.0%
Uppercase Letter
ValueCountFrequency (%)
N2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2954
99.2%
Latin23
 
0.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3
13.0%
o2
 
8.7%
n2
 
8.7%
d2
 
8.7%
s2
 
8.7%
N2
 
8.7%
b1
 
4.3%
v1
 
4.3%
g1
 
4.3%
l1
 
4.3%
Other values (6)6
26.1%
Common
ValueCountFrequency (%)
02044
69.2%
5203
 
6.9%
1195
 
6.6%
2130
 
4.4%
785
 
2.9%
671
 
2.4%
369
 
2.3%
466
 
2.2%
852
 
1.8%
932
 
1.1%
Other values (4)7
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII2977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02044
68.7%
5203
 
6.8%
1195
 
6.6%
2130
 
4.4%
785
 
2.9%
671
 
2.4%
369
 
2.3%
466
 
2.2%
852
 
1.7%
932
 
1.1%
Other values (20)30
 
1.0%

Annual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same country
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct147
Distinct (%)16.6%
Missing2124
Missing (%)70.6%
Infinite0
Infinite (%)0.0%
Mean632245.8723
Minimum11000
Maximum500000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum11000
5-th percentile37000
Q155000
median65000
Q375000
95-th percentile98000
Maximum500000000
Range499989000
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation16805081.75
Coefficient of variation (CV)26.57997859
Kurtosis884.9937503
Mean632245.8723
Median Absolute Deviation (MAD)10000
Skewness29.74879226
Sum559537597
Variance2.824107727 × 1014
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6500069
 
2.3%
6000065
 
2.2%
7500052
 
1.7%
7000048
 
1.6%
5500042
 
1.4%
8000042
 
1.4%
7200024
 
0.8%
8500022
 
0.7%
5000021
 
0.7%
9000021
 
0.7%
Other values (137)479
 
15.9%
(Missing)2124
70.6%
ValueCountFrequency (%)
110001
< 0.1%
120002
0.1%
147121
< 0.1%
150001
< 0.1%
160002
0.1%
165601
< 0.1%
170001
< 0.1%
180001
< 0.1%
190001
< 0.1%
200002
0.1%
ValueCountFrequency (%)
5000000001
< 0.1%
7600001
< 0.1%
2300001
< 0.1%
2000002
0.1%
1900001
< 0.1%
1690001
< 0.1%
1600001
< 0.1%
1560001
< 0.1%
1400002
0.1%
1320001
< 0.1%
Distinct131
Distinct (%)21.3%
Missing2395
Missing (%)79.6%
Memory size23.6 KiB
0
200 
5000
 
32
10000
 
25
60000
 
15
3000
 
13
Other values (126)
329 

Length

Max length31
Median length4
Mean length3.446254072
Min length1

Characters and Unicode

Total characters2116
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)10.4%

Sample

1st row10000
2nd row5000
3rd row100000
4th row5000
5th row13000

Common Values

ValueCountFrequency (%)
0200
 
6.6%
500032
 
1.1%
1000025
 
0.8%
6000015
 
0.5%
300013
 
0.4%
100013
 
0.4%
600012
 
0.4%
700012
 
0.4%
200011
 
0.4%
8000010
 
0.3%
Other values (121)271
 
9.0%
(Missing)2395
79.6%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
0200
32.4%
500032
 
5.2%
1000025
 
4.0%
6000015
 
2.4%
100013
 
2.1%
300013
 
2.1%
700012
 
1.9%
600012
 
1.9%
200011
 
1.8%
8000010
 
1.6%
Other values (125)275
44.5%

Most occurring characters

ValueCountFrequency (%)
01462
69.1%
5144
 
6.8%
1104
 
4.9%
673
 
3.4%
268
 
3.2%
759
 
2.8%
356
 
2.6%
856
 
2.6%
444
 
2.1%
918
 
0.9%
Other values (19)32
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2084
98.5%
Lowercase Letter24
 
1.1%
Space Separator4
 
0.2%
Other Punctuation3
 
0.1%
Dash Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g4
16.7%
e2
 
8.3%
n2
 
8.3%
b2
 
8.3%
d2
 
8.3%
o2
 
8.3%
l1
 
4.2%
a1
 
4.2%
r1
 
4.2%
i1
 
4.2%
Other values (6)6
25.0%
Decimal Number
ValueCountFrequency (%)
01462
70.2%
5144
 
6.9%
1104
 
5.0%
673
 
3.5%
268
 
3.3%
759
 
2.8%
356
 
2.7%
856
 
2.7%
444
 
2.1%
918
 
0.9%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
,3
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2092
98.9%
Latin24
 
1.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
g4
16.7%
e2
 
8.3%
n2
 
8.3%
b2
 
8.3%
d2
 
8.3%
o2
 
8.3%
l1
 
4.2%
a1
 
4.2%
r1
 
4.2%
i1
 
4.2%
Other values (6)6
25.0%
Common
ValueCountFrequency (%)
01462
69.9%
5144
 
6.9%
1104
 
5.0%
673
 
3.5%
268
 
3.3%
759
 
2.8%
356
 
2.7%
856
 
2.7%
444
 
2.1%
918
 
0.9%
Other values (3)8
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII2116
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01462
69.1%
5144
 
6.8%
1104
 
4.9%
673
 
3.4%
268
 
3.2%
759
 
2.8%
356
 
2.6%
856
 
2.6%
444
 
2.1%
918
 
0.9%
Other values (19)32
 
1.5%

Number of vacation days
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing893
Missing (%)29.7%
Memory size23.6 KiB

Employment status
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)0.9%
Missing1773
Missing (%)58.9%
Memory size23.6 KiB
Full-time employee
1190 
Self-employed (freelancer)
 
28
Part-time employee
 
8
Founder
 
3
Werkstudent
 
1
Other values (6)
 
6

Length

Max length79
Median length18
Mean length18.22168285
Min length6

Characters and Unicode

Total characters22522
Distinct characters38
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.6%

Sample

1st rowFull-time employee
2nd rowFull-time employee
3rd rowSelf-employed (freelancer)
4th rowFull-time employee
5th rowFull-time employee

Common Values

ValueCountFrequency (%)
Full-time employee1190
39.5%
Self-employed (freelancer)28
 
0.9%
Part-time employee8
 
0.3%
Founder3
 
0.1%
Werkstudent1
 
< 0.1%
Full-time position, part-time position, & self-employed (freelancing, tutoring)1
 
< 0.1%
working student1
 
< 0.1%
full-time, but 32 hours per week (it was my request, I'm a student)1
 
< 0.1%
Company Director1
 
< 0.1%
Working Student1
 
< 0.1%
(Missing)1773
58.9%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
employee1198
48.2%
full-time1192
48.0%
self-employed29
 
1.2%
freelancer28
 
1.1%
part-time9
 
0.4%
founder3
 
0.1%
student3
 
0.1%
working2
 
0.1%
position2
 
0.1%
werkstudent1
 
< 0.1%
Other values (17)17
 
0.7%

Most occurring characters

ValueCountFrequency (%)
e4983
22.1%
l3669
16.3%
m2431
10.8%
1248
 
5.5%
o1240
 
5.5%
p1232
 
5.5%
-1230
 
5.5%
y1229
 
5.5%
t1227
 
5.4%
i1211
 
5.4%
Other values (28)2822
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter18738
83.2%
Space Separator1248
 
5.5%
Uppercase Letter1237
 
5.5%
Dash Punctuation1230
 
5.5%
Open Punctuation30
 
0.1%
Close Punctuation30
 
0.1%
Other Punctuation7
 
< 0.1%
Decimal Number2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e4983
26.6%
l3669
19.6%
m2431
13.0%
o1240
 
6.6%
p1232
 
6.6%
y1229
 
6.6%
t1227
 
6.5%
i1211
 
6.5%
u1203
 
6.4%
r79
 
0.4%
Other values (12)234
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
F1194
96.5%
S29
 
2.3%
P8
 
0.6%
W2
 
0.2%
I2
 
0.2%
C1
 
0.1%
D1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
,5
71.4%
&1
 
14.3%
'1
 
14.3%
Decimal Number
ValueCountFrequency (%)
31
50.0%
21
50.0%
Dash Punctuation
ValueCountFrequency (%)
-1230
100.0%
Space Separator
ValueCountFrequency (%)
1248
100.0%
Open Punctuation
ValueCountFrequency (%)
(30
100.0%
Close Punctuation
ValueCountFrequency (%)
)30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin19975
88.7%
Common2547
 
11.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e4983
24.9%
l3669
18.4%
m2431
12.2%
o1240
 
6.2%
p1232
 
6.2%
y1229
 
6.2%
t1227
 
6.1%
i1211
 
6.1%
u1203
 
6.0%
F1194
 
6.0%
Other values (19)356
 
1.8%
Common
ValueCountFrequency (%)
1248
49.0%
-1230
48.3%
(30
 
1.2%
)30
 
1.2%
,5
 
0.2%
&1
 
< 0.1%
31
 
< 0.1%
21
 
< 0.1%
'1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII22522
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e4983
22.1%
l3669
16.3%
m2431
10.8%
1248
 
5.5%
o1240
 
5.5%
p1232
 
5.5%
-1230
 
5.5%
y1229
 
5.5%
t1227
 
5.4%
i1211
 
5.4%
Other values (28)2822
12.5%

Сontract duration
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)0.4%
Missing823
Missing (%)27.4%
Memory size23.6 KiB
Unlimited contract
1159 
unlimited
851 
Temporary contract
 
64
more than 1 year
 
59
1 year
 
40
Other values (4)
 
13

Length

Max length18
Median length18
Mean length14.16468435
Min length1

Characters and Unicode

Total characters30964
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st rowUnlimited contract
2nd rowUnlimited contract
3rd rowTemporary contract
4th rowUnlimited contract
5th rowUnlimited contract

Common Values

ValueCountFrequency (%)
Unlimited contract1159
38.5%
unlimited851
28.3%
Temporary contract64
 
2.1%
more than 1 year59
 
2.0%
1 year40
 
1.3%
6 months7
 
0.2%
3 months4
 
0.1%
01
 
< 0.1%
less than 3 months1
 
< 0.1%
(Missing)823
27.4%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
unlimited2010
55.2%
contract1223
33.6%
199
 
2.7%
year99
 
2.7%
temporary64
 
1.8%
than60
 
1.6%
more59
 
1.6%
months12
 
0.3%
67
 
0.2%
35
 
0.1%
Other values (2)2
 
0.1%

Most occurring characters

ValueCountFrequency (%)
t4528
14.6%
i4020
13.0%
n3305
10.7%
c2446
7.9%
e2233
7.2%
m2145
6.9%
l2011
 
6.5%
d2010
 
6.5%
r1509
 
4.9%
1454
 
4.7%
Other values (13)5303
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter28175
91.0%
Space Separator1454
 
4.7%
Uppercase Letter1223
 
3.9%
Decimal Number112
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t4528
16.1%
i4020
14.3%
n3305
11.7%
c2446
8.7%
e2233
7.9%
m2145
7.6%
l2011
7.1%
d2010
7.1%
r1509
 
5.4%
a1446
 
5.1%
Other values (6)2522
9.0%
Decimal Number
ValueCountFrequency (%)
199
88.4%
67
 
6.2%
35
 
4.5%
01
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
U1159
94.8%
T64
 
5.2%
Space Separator
ValueCountFrequency (%)
1454
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin29398
94.9%
Common1566
 
5.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t4528
15.4%
i4020
13.7%
n3305
11.2%
c2446
8.3%
e2233
7.6%
m2145
7.3%
l2011
6.8%
d2010
6.8%
r1509
 
5.1%
a1446
 
4.9%
Other values (8)3745
12.7%
Common
ValueCountFrequency (%)
1454
92.8%
199
 
6.3%
67
 
0.4%
35
 
0.3%
01
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII30964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t4528
14.6%
i4020
13.0%
n3305
10.7%
c2446
7.9%
e2233
7.2%
m2145
6.9%
l2011
 
6.5%
d2010
 
6.5%
r1509
 
4.9%
1454
 
4.7%
Other values (13)5303
17.1%

Main language at work
Categorical

HIGH CORRELATION
MISSING

Distinct21
Distinct (%)0.7%
Missing36
Missing (%)1.2%
Memory size23.6 KiB
English
2354 
Deutsch
316 
German
 
186
Russian
 
78
French
 
8
Other values (16)
 
31

Length

Max length37
Median length7
Mean length6.958964009
Min length4

Characters and Unicode

Total characters20689
Distinct characters44
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.3%

Sample

1st rowEnglish
2nd rowEnglish
3rd rowEnglish
4th rowEnglish
5th rowEnglish

Common Values

ValueCountFrequency (%)
English2354
78.2%
Deutsch316
 
10.5%
German186
 
6.2%
Russian78
 
2.6%
French8
 
0.3%
Polish6
 
0.2%
Italian5
 
0.2%
Spanish4
 
0.1%
Русский2
 
0.1%
English and German2
 
0.1%
Other values (11)12
 
0.4%
(Missing)36
 
1.2%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
english2358
79.0%
deutsch316
 
10.6%
german188
 
6.3%
russian80
 
2.7%
french8
 
0.3%
polish6
 
0.2%
italian5
 
0.2%
spanish4
 
0.1%
2
 
0.1%
czech2
 
0.1%
Other values (12)14
 
0.5%

Most occurring characters

ValueCountFrequency (%)
s2853
13.8%
h2703
13.1%
n2650
12.8%
i2460
11.9%
l2374
11.5%
g2362
11.4%
E2361
11.4%
e519
 
2.5%
u400
 
1.9%
c331
 
1.6%
Other values (34)1676
8.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter17685
85.5%
Uppercase Letter2980
 
14.4%
Space Separator10
 
< 0.1%
Other Punctuation5
 
< 0.1%
Decimal Number4
 
< 0.1%
Dash Punctuation3
 
< 0.1%
Math Symbol2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s2853
16.1%
h2703
15.3%
n2650
15.0%
i2460
13.9%
l2374
13.4%
g2362
13.4%
e519
 
2.9%
u400
 
2.3%
c331
 
1.9%
t326
 
1.8%
Other values (14)707
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
E2361
79.2%
D320
 
10.7%
G188
 
6.3%
R80
 
2.7%
F8
 
0.3%
P7
 
0.2%
I5
 
0.2%
S4
 
0.1%
C3
 
0.1%
Р2
 
0.1%
Other values (2)2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/2
40.0%
;2
40.0%
,1
20.0%
Decimal Number
ValueCountFrequency (%)
52
50.0%
02
50.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Math Symbol
ValueCountFrequency (%)
+2
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin20651
99.8%
Common24
 
0.1%
Cyrillic14
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s2853
13.8%
h2703
13.1%
n2650
12.8%
i2460
11.9%
l2374
11.5%
g2362
11.4%
E2361
11.4%
e519
 
2.5%
u400
 
1.9%
c331
 
1.6%
Other values (20)1638
7.9%
Common
ValueCountFrequency (%)
10
41.7%
-3
 
12.5%
52
 
8.3%
02
 
8.3%
/2
 
8.3%
+2
 
8.3%
;2
 
8.3%
,1
 
4.2%
Cyrillic
ValueCountFrequency (%)
с4
28.6%
Р2
14.3%
у2
14.3%
к2
14.3%
и2
14.3%
й2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII20675
99.9%
Cyrillic14
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s2853
13.8%
h2703
13.1%
n2650
12.8%
i2460
11.9%
l2374
11.5%
g2362
11.4%
E2361
11.4%
e519
 
2.5%
u400
 
1.9%
c331
 
1.6%
Other values (28)1662
8.0%
Cyrillic
ValueCountFrequency (%)
с4
28.6%
Р2
14.3%
у2
14.3%
к2
14.3%
и2
14.3%
й2
14.3%

Company size
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)0.3%
Missing47
Missing (%)1.6%
Memory size23.6 KiB
1000+
1013 
100-1000
626 
101-1000
405 
50-100
252 
10-50
222 
Other values (3)
444 

Length

Max length8
Median length6
Mean length6.303511141
Min length5

Characters and Unicode

Total characters18671
Distinct characters10
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row51-100
2nd row101-1000
3rd row101-1000
4th row51-100
5th row101-1000

Common Values

ValueCountFrequency (%)
1000+1013
33.7%
100-1000626
20.8%
101-1000405
 
13.5%
50-100252
 
8.4%
10-50222
 
7.4%
11-50174
 
5.8%
51-100147
 
4.9%
up to 10123
 
4.1%
(Missing)47
 
1.6%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
10001013
31.6%
100-1000626
19.5%
101-1000405
 
12.6%
50-100252
 
7.9%
10-50222
 
6.9%
11-50174
 
5.4%
51-100147
 
4.6%
10123
 
3.8%
up123
 
3.8%
to123
 
3.8%

Most occurring characters

ValueCountFrequency (%)
09580
51.3%
14719
25.3%
-1826
 
9.8%
+1013
 
5.4%
5795
 
4.3%
246
 
1.3%
u123
 
0.7%
p123
 
0.7%
t123
 
0.7%
o123
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number15094
80.8%
Dash Punctuation1826
 
9.8%
Math Symbol1013
 
5.4%
Lowercase Letter492
 
2.6%
Space Separator246
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u123
25.0%
p123
25.0%
t123
25.0%
o123
25.0%
Decimal Number
ValueCountFrequency (%)
09580
63.5%
14719
31.3%
5795
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
-1826
100.0%
Math Symbol
ValueCountFrequency (%)
+1013
100.0%
Space Separator
ValueCountFrequency (%)
246
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common18179
97.4%
Latin492
 
2.6%

Most frequent character per script

Common
ValueCountFrequency (%)
09580
52.7%
14719
26.0%
-1826
 
10.0%
+1013
 
5.6%
5795
 
4.4%
246
 
1.4%
Latin
ValueCountFrequency (%)
u123
25.0%
p123
25.0%
t123
25.0%
o123
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII18671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
09580
51.3%
14719
25.3%
-1826
 
9.8%
+1013
 
5.4%
5795
 
4.3%
246
 
1.3%
u123
 
0.7%
p123
 
0.7%
t123
 
0.7%
o123
 
0.7%

Company type
Categorical

HIGH CARDINALITY
MISSING

Distinct101
Distinct (%)3.5%
Missing91
Missing (%)3.0%
Memory size23.6 KiB
Product
1830 
Startup
578 
Consulting / Agency
259 
Agency
 
74
Bodyshop / Outsource
 
30
Other values (96)
 
147

Length

Max length72
Median length7
Mean length8.393420151
Min length3

Characters and Unicode

Total characters24492
Distinct characters49
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)2.5%

Sample

1st rowProduct
2nd rowProduct
3rd rowProduct
4th rowStartup
5th rowProduct

Common Values

ValueCountFrequency (%)
Product1830
60.8%
Startup578
 
19.2%
Consulting / Agency259
 
8.6%
Agency74
 
2.5%
Bodyshop / Outsource30
 
1.0%
Bank11
 
0.4%
University8
 
0.3%
Outsource6
 
0.2%
Consulting5
 
0.2%
Corporation4
 
0.1%
Other values (91)113
 
3.8%
(Missing)91
 
3.0%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
product1832
51.5%
startup579
 
16.3%
agency333
 
9.4%
290
 
8.2%
consulting271
 
7.6%
outsource37
 
1.0%
bodyshop30
 
0.8%
bank13
 
0.4%
e-commerce8
 
0.2%
university8
 
0.2%
Other values (98)153
 
4.3%

Most occurring characters

ValueCountFrequency (%)
t3403
13.9%
u2808
11.5%
r2541
10.4%
o2304
9.4%
c2279
9.3%
d1888
 
7.7%
P1841
 
7.5%
n997
 
4.1%
a666
 
2.7%
651
 
2.7%
Other values (39)5114
20.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter20285
82.8%
Uppercase Letter3245
 
13.2%
Space Separator651
 
2.7%
Other Punctuation293
 
1.2%
Dash Punctuation16
 
0.1%
Open Punctuation1
 
< 0.1%
Close Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t3403
16.8%
u2808
13.8%
r2541
12.5%
o2304
11.4%
c2279
11.2%
d1888
9.3%
n997
 
4.9%
a666
 
3.3%
p630
 
3.1%
g623
 
3.1%
Other values (14)2146
10.6%
Uppercase Letter
ValueCountFrequency (%)
P1841
56.7%
S586
 
18.1%
A339
 
10.4%
C289
 
8.9%
B50
 
1.5%
O45
 
1.4%
I20
 
0.6%
T17
 
0.5%
E14
 
0.4%
U10
 
0.3%
Other values (8)34
 
1.0%
Other Punctuation
ValueCountFrequency (%)
/290
99.0%
,2
 
0.7%
&1
 
0.3%
Space Separator
ValueCountFrequency (%)
651
100.0%
Dash Punctuation
ValueCountFrequency (%)
-16
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin23530
96.1%
Common962
 
3.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t3403
14.5%
u2808
11.9%
r2541
10.8%
o2304
9.8%
c2279
9.7%
d1888
8.0%
P1841
7.8%
n997
 
4.2%
a666
 
2.8%
p630
 
2.7%
Other values (32)4173
17.7%
Common
ValueCountFrequency (%)
651
67.7%
/290
30.1%
-16
 
1.7%
,2
 
0.2%
&1
 
0.1%
(1
 
0.1%
)1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII24491
> 99.9%
Latin 1 Sup1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t3403
13.9%
u2808
11.5%
r2541
10.4%
o2304
9.4%
c2279
9.3%
d1888
 
7.7%
P1841
 
7.5%
n997
 
4.1%
a666
 
2.7%
651
 
2.7%
Other values (38)5113
20.9%
Latin 1 Sup
ValueCountFrequency (%)
ö1
100.0%
Distinct10
Distinct (%)0.8%
Missing1776
Missing (%)59.0%
Memory size23.6 KiB
No
1162 
Yes
 
63
i didn't but will be looking for new one because of covid
 
1
Laid off for a bit
 
1
Leads and project inquiries have slowed down
 
1
Other values (5)
 
5

Length

Max length86
Median length2
Mean length2.334144363
Min length2

Characters and Unicode

Total characters2878
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.6%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No1162
38.6%
Yes63
 
2.1%
i didn't but will be looking for new one because of covid1
 
< 0.1%
Laid off for a bit1
 
< 0.1%
Leads and project inquiries have slowed down1
 
< 0.1%
Lost the job but for different reason1
 
< 0.1%
kurzarbeitzeit for 1.5 months1
 
< 0.1%
yes but found a new one with better pay / perks1
 
< 0.1%
Have been a freelancer at the beginning of year1
 
< 0.1%
No, but there was a salary cut at 10% for 3 months and then at 5% for further 3 months1
 
< 0.1%
(Missing)1776
59.0%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
no1163
89.5%
yes64
 
4.9%
for6
 
0.5%
a4
 
0.3%
but4
 
0.3%
at3
 
0.2%
months3
 
0.2%
the2
 
0.2%
and2
 
0.2%
of2
 
0.2%
Other values (43)47
 
3.6%

Most occurring characters

ValueCountFrequency (%)
o1187
41.2%
N1163
40.4%
e98
 
3.4%
s76
 
2.6%
67
 
2.3%
Y63
 
2.2%
t26
 
0.9%
n22
 
0.8%
a22
 
0.8%
r21
 
0.7%
Other values (29)133
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1568
54.5%
Uppercase Letter1230
42.7%
Space Separator67
 
2.3%
Decimal Number7
 
0.2%
Other Punctuation6
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o1187
75.7%
e98
 
6.2%
s76
 
4.8%
t26
 
1.7%
n22
 
1.4%
a22
 
1.4%
r21
 
1.3%
i16
 
1.0%
f15
 
1.0%
b12
 
0.8%
Other values (15)73
 
4.7%
Other Punctuation
ValueCountFrequency (%)
%2
33.3%
'1
16.7%
.1
16.7%
,1
16.7%
/1
16.7%
Uppercase Letter
ValueCountFrequency (%)
N1163
94.6%
Y63
 
5.1%
L3
 
0.2%
H1
 
0.1%
Decimal Number
ValueCountFrequency (%)
12
28.6%
52
28.6%
32
28.6%
01
14.3%
Space Separator
ValueCountFrequency (%)
67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2798
97.2%
Common80
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o1187
42.4%
N1163
41.6%
e98
 
3.5%
s76
 
2.7%
Y63
 
2.3%
t26
 
0.9%
n22
 
0.8%
a22
 
0.8%
r21
 
0.8%
i16
 
0.6%
Other values (19)104
 
3.7%
Common
ValueCountFrequency (%)
67
83.8%
12
 
2.5%
52
 
2.5%
%2
 
2.5%
32
 
2.5%
'1
 
1.2%
.1
 
1.2%
,1
 
1.2%
01
 
1.2%
/1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII2878
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o1187
41.2%
N1163
40.4%
e98
 
3.4%
s76
 
2.6%
67
 
2.3%
Y63
 
2.2%
t26
 
0.9%
n22
 
0.8%
a22
 
0.8%
r21
 
0.7%
Other values (29)133
 
4.6%
Distinct23
Distinct (%)6.2%
Missing2636
Missing (%)87.6%
Infinite0
Infinite (%)0.0%
Mean12.96782842
Minimum0
Maximum40
Zeros197
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q330
95-th percentile40
Maximum40
Range40
Interquartile range (IQR)30

Descriptive statistics

Standard deviation15.27517435
Coefficient of variation (CV)1.177928475
Kurtosis-1.430155043
Mean12.96782842
Median Absolute Deviation (MAD)0
Skewness0.5374225668
Sum4837
Variance233.3309515
MonotonicityNot monotonic
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0197
 
6.5%
3032
 
1.1%
3231
 
1.0%
2028
 
0.9%
4027
 
0.9%
88
 
0.3%
248
 
0.3%
287
 
0.2%
106
 
0.2%
365
 
0.2%
Other values (13)24
 
0.8%
(Missing)2636
87.6%
ValueCountFrequency (%)
0197
6.5%
21
 
< 0.1%
43
 
0.1%
52
 
0.1%
88
 
0.3%
106
 
0.2%
121
 
< 0.1%
151
 
< 0.1%
161
 
< 0.1%
2028
 
0.9%
ValueCountFrequency (%)
4027
0.9%
391
 
< 0.1%
381
 
< 0.1%
37.52
 
0.1%
365
 
0.2%
354
 
0.1%
342
 
0.1%
3231
1.0%
3032
1.1%
287
 
0.2%
Distinct59
Distinct (%)12.8%
Missing2547
Missing (%)84.6%
Memory size23.6 KiB
0
161 
500
47 
No
33 
1000
23 
600
20 
Other values (54)
178 

Length

Max length55
Median length3
Mean length2.582251082
Min length1

Characters and Unicode

Total characters1193
Distinct characters44
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)6.7%

Sample

1st row600
2nd row1000
3rd row200
4th row1100
5th row1

Common Values

ValueCountFrequency (%)
0161
 
5.4%
50047
 
1.6%
No33
 
1.1%
100023
 
0.8%
60020
 
0.7%
20019
 
0.6%
150019
 
0.6%
30018
 
0.6%
70014
 
0.5%
40012
 
0.4%
Other values (49)96
 
3.2%
(Missing)2547
84.6%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
0161
33.3%
50047
 
9.7%
no40
 
8.3%
100023
 
4.8%
60021
 
4.3%
20020
 
4.1%
150019
 
3.9%
30018
 
3.7%
70014
 
2.9%
40013
 
2.7%
Other values (60)107
22.2%

Most occurring characters

ValueCountFrequency (%)
0663
55.6%
596
 
8.0%
177
 
6.5%
o52
 
4.4%
239
 
3.3%
N33
 
2.8%
629
 
2.4%
425
 
2.1%
322
 
1.8%
22
 
1.8%
Other values (34)135
 
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number992
83.2%
Lowercase Letter136
 
11.4%
Uppercase Letter36
 
3.0%
Space Separator22
 
1.8%
Other Punctuation5
 
0.4%
Currency Symbol1
 
0.1%
Dash Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o52
38.2%
n15
 
11.0%
e14
 
10.3%
t9
 
6.6%
m8
 
5.9%
r5
 
3.7%
h4
 
2.9%
v4
 
2.9%
a4
 
2.9%
l3
 
2.2%
Other values (14)18
 
13.2%
Decimal Number
ValueCountFrequency (%)
0663
66.8%
596
 
9.7%
177
 
7.8%
239
 
3.9%
629
 
2.9%
425
 
2.5%
322
 
2.2%
721
 
2.1%
816
 
1.6%
94
 
0.4%
Other Punctuation
ValueCountFrequency (%)
%2
40.0%
/1
20.0%
.1
20.0%
,1
20.0%
Uppercase Letter
ValueCountFrequency (%)
N33
91.7%
I2
 
5.6%
A1
 
2.8%
Currency Symbol
ValueCountFrequency (%)
1
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1021
85.6%
Latin172
 
14.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o52
30.2%
N33
19.2%
n15
 
8.7%
e14
 
8.1%
t9
 
5.2%
m8
 
4.7%
r5
 
2.9%
h4
 
2.3%
v4
 
2.3%
a4
 
2.3%
Other values (17)24
14.0%
Common
ValueCountFrequency (%)
0663
64.9%
596
 
9.4%
177
 
7.5%
239
 
3.8%
629
 
2.8%
425
 
2.4%
322
 
2.2%
22
 
2.2%
721
 
2.1%
816
 
1.6%
Other values (7)11
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1192
99.9%
Currency Symbols1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0663
55.6%
596
 
8.1%
177
 
6.5%
o52
 
4.4%
239
 
3.3%
N33
 
2.8%
629
 
2.4%
425
 
2.1%
322
 
1.8%
22
 
1.8%
Other values (33)134
 
11.2%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

Zeitstempel
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct991
Distinct (%)100.0%
Missing2018
Missing (%)67.1%
Memory size23.6 KiB
02.12.2019 17:50:19
 
1
02.12.2019 15:44:44
 
1
04.12.2019 21:53:33
 
1
02.12.2019 11:32:59
 
1
02.12.2019 11:49:02
 
1
Other values (986)
986 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters18829
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique991 ?
Unique (%)100.0%

Sample

1st row02.12.2019 11:18:26
2nd row02.12.2019 11:18:35
3rd row02.12.2019 11:18:56
4th row02.12.2019 11:19:08
5th row02.12.2019 11:19:37

Common Values

ValueCountFrequency (%)
02.12.2019 17:50:191
 
< 0.1%
02.12.2019 15:44:441
 
< 0.1%
04.12.2019 21:53:331
 
< 0.1%
02.12.2019 11:32:591
 
< 0.1%
02.12.2019 11:49:021
 
< 0.1%
02.12.2019 19:48:291
 
< 0.1%
03.12.2019 12:03:111
 
< 0.1%
06.12.2019 14:18:141
 
< 0.1%
06.12.2019 10:19:221
 
< 0.1%
10.12.2019 17:42:561
 
< 0.1%
Other values (981)981
32.6%
(Missing)2018
67.1%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
02.12.2019266
 
13.4%
04.12.2019126
 
6.4%
03.12.2019119
 
6.0%
05.12.201998
 
4.9%
10.12.201967
 
3.4%
11.12.201947
 
2.4%
20.12.201945
 
2.3%
06.12.201940
 
2.0%
09.12.201920
 
1.0%
08.12.201917
 
0.9%
Other values (1012)1137
57.4%

Most occurring characters

ValueCountFrequency (%)
13585
19.0%
23190
16.9%
02658
14.1%
.1982
10.5%
:1982
10.5%
91293
 
6.9%
991
 
5.3%
3779
 
4.1%
5741
 
3.9%
4728
 
3.9%
Other values (3)900
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number13874
73.7%
Other Punctuation3964
 
21.1%
Space Separator991
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
13585
25.8%
23190
23.0%
02658
19.2%
91293
 
9.3%
3779
 
5.6%
5741
 
5.3%
4728
 
5.2%
6338
 
2.4%
8285
 
2.1%
7277
 
2.0%
Other Punctuation
ValueCountFrequency (%)
.1982
50.0%
:1982
50.0%
Space Separator
ValueCountFrequency (%)
991
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common18829
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
13585
19.0%
23190
16.9%
02658
14.1%
.1982
10.5%
:1982
10.5%
91293
 
6.9%
991
 
5.3%
3779
 
4.1%
5741
 
3.9%
4728
 
3.9%
Other values (3)900
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII18829
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13585
19.0%
23190
16.9%
02658
14.1%
.1982
10.5%
:1982
10.5%
91293
 
6.9%
991
 
5.3%
3779
 
4.1%
5741
 
3.9%
4728
 
3.9%
Other values (3)900
 
4.8%

Position (without seniority)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct51
Distinct (%)5.2%
Missing2019
Missing (%)67.1%
Memory size23.6 KiB
Backend Developer
253 
Data Scientist
122 
Fullstack Developer
78 
Frontend Developer
68 
Manager
63 
Other values (46)
406 

Length

Max length29
Median length17
Mean length14.51111111
Min length2

Characters and Unicode

Total characters14366
Distinct characters50
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)2.2%

Sample

1st rowFullstack Developer
2nd rowBackend Developer
3rd rowMobile Developer
4th rowBackend Developer
5th rowEmbedded Developer

Common Values

ValueCountFrequency (%)
Backend Developer253
 
8.4%
Data Scientist122
 
4.1%
Fullstack Developer78
 
2.6%
Frontend Developer68
 
2.3%
Manager63
 
2.1%
QA56
 
1.9%
DevOps53
 
1.8%
Mobile Developer46
 
1.5%
Data Engineer39
 
1.3%
Software Architect36
 
1.2%
Other values (41)176
 
5.8%
(Missing)2019
67.1%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
developer467
25.5%
backend254
13.8%
data162
 
8.8%
scientist122
 
6.7%
engineer92
 
5.0%
fullstack78
 
4.3%
manager74
 
4.0%
frontend68
 
3.7%
qa56
 
3.1%
devops54
 
2.9%
Other values (53)407
22.2%

Most occurring characters

ValueCountFrequency (%)
e2483
17.3%
a994
 
6.9%
n946
 
6.6%
r895
 
6.2%
846
 
5.9%
t768
 
5.3%
l715
 
5.0%
D695
 
4.8%
o682
 
4.7%
c594
 
4.1%
Other values (40)4748
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter11435
79.6%
Uppercase Letter2043
 
14.2%
Space Separator846
 
5.9%
Open Punctuation14
 
0.1%
Close Punctuation14
 
0.1%
Other Punctuation13
 
0.1%
Decimal Number1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2483
21.7%
a994
8.7%
n946
 
8.3%
r895
 
7.8%
t768
 
6.7%
l715
 
6.3%
o682
 
6.0%
c594
 
5.2%
i536
 
4.7%
p535
 
4.7%
Other values (13)2287
20.0%
Uppercase Letter
ValueCountFrequency (%)
D695
34.0%
B274
 
13.4%
S203
 
9.9%
M155
 
7.6%
F153
 
7.5%
A133
 
6.5%
E125
 
6.1%
O75
 
3.7%
Q56
 
2.7%
L40
 
2.0%
Other values (10)134
 
6.6%
Other Punctuation
ValueCountFrequency (%)
,11
84.6%
/1
 
7.7%
&1
 
7.7%
Space Separator
ValueCountFrequency (%)
846
100.0%
Open Punctuation
ValueCountFrequency (%)
(14
100.0%
Close Punctuation
ValueCountFrequency (%)
)14
100.0%
Decimal Number
ValueCountFrequency (%)
31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin13478
93.8%
Common888
 
6.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2483
18.4%
a994
 
7.4%
n946
 
7.0%
r895
 
6.6%
t768
 
5.7%
l715
 
5.3%
D695
 
5.2%
o682
 
5.1%
c594
 
4.4%
i536
 
4.0%
Other values (33)4170
30.9%
Common
ValueCountFrequency (%)
846
95.3%
(14
 
1.6%
)14
 
1.6%
,11
 
1.2%
/1
 
0.1%
31
 
0.1%
&1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII14366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e2483
17.3%
a994
 
6.9%
n946
 
6.6%
r895
 
6.2%
846
 
5.9%
t768
 
5.3%
l715
 
5.0%
D695
 
4.8%
o682
 
4.7%
c594
 
4.1%
Other values (40)4748
33.1%

Years of experience
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct33
Distinct (%)1.9%
Missing1286
Missing (%)42.7%
Infinite0
Infinite (%)0.0%
Mean8.537724898
Minimum0
Maximum38
Zeros9
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum0
5-th percentile2
Q15
median8
Q311
95-th percentile18
Maximum38
Range38
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.906947591
Coefficient of variation (CV)0.5747371401
Kurtosis1.436354784
Mean8.537724898
Median Absolute Deviation (MAD)3
Skewness0.8812288078
Sum14710.5
Variance24.07813466
MonotonicityNot monotonic
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
10213
 
7.1%
5164
 
5.5%
8148
 
4.9%
7135
 
4.5%
6123
 
4.1%
3108
 
3.6%
4103
 
3.4%
1297
 
3.2%
991
 
3.0%
1590
 
3.0%
Other values (23)451
 
15.0%
(Missing)1286
42.7%
ValueCountFrequency (%)
09
 
0.3%
0.52
 
0.1%
162
 
2.1%
1.52
 
0.1%
272
2.4%
2.55
 
0.2%
3108
3.6%
4103
3.4%
4.51
 
< 0.1%
5164
5.5%
ValueCountFrequency (%)
381
 
< 0.1%
303
 
0.1%
282
 
0.1%
258
 
0.3%
241
 
< 0.1%
224
 
0.1%
211
 
< 0.1%
2036
1.2%
1911
 
0.4%
1828
0.9%

Yearly brutto salary (without bonus and stocks)
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct173
Distinct (%)17.5%
Missing2019
Missing (%)67.1%
Infinite0
Infinite (%)0.0%
Mean72562.21212
Minimum6000
Maximum216000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum6000
5-th percentile42000
Q160000
median70000
Q380000
95-th percentile118650
Maximum216000
Range210000
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation23947.37918
Coefficient of variation (CV)0.3300254841
Kurtosis5.61555162
Mean72562.21212
Median Absolute Deviation (MAD)10000
Skewness1.534901428
Sum71836590
Variance573476969.7
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7000063
 
2.1%
6500059
 
2.0%
6000053
 
1.8%
7500053
 
1.8%
8000037
 
1.2%
5500033
 
1.1%
7200027
 
0.9%
6800025
 
0.8%
6200024
 
0.8%
9000022
 
0.7%
Other values (163)594
 
19.7%
(Missing)2019
67.1%
ValueCountFrequency (%)
60001
< 0.1%
132001
< 0.1%
140001
< 0.1%
144001
< 0.1%
156001
< 0.1%
200001
< 0.1%
216002
0.1%
220001
< 0.1%
235001
< 0.1%
240002
0.1%
ValueCountFrequency (%)
2160001
 
< 0.1%
2100002
0.1%
2000001
 
< 0.1%
1900001
 
< 0.1%
1750001
 
< 0.1%
1700001
 
< 0.1%
1600003
0.1%
1550001
 
< 0.1%
1500004
0.1%
1400002
0.1%

Yearly bonus
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct91
Distinct (%)17.2%
Missing2479
Missing (%)82.4%
Infinite0
Infinite (%)0.0%
Mean7857.169811
Minimum0
Maximum80000
Zeros123
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum0
5-th percentile0
Q1300
median5000
Q310000
95-th percentile25000
Maximum80000
Range80000
Interquartile range (IQR)9700

Descriptive statistics

Standard deviation10320.62834
Coefficient of variation (CV)1.31353001
Kurtosis12.85681305
Mean7857.169811
Median Absolute Deviation (MAD)5000
Skewness2.975022003
Sum4164300
Variance106515369.4
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0123
 
4.1%
500056
 
1.9%
300030
 
1.0%
1000026
 
0.9%
600020
 
0.7%
700017
 
0.6%
1200016
 
0.5%
2500016
 
0.5%
400015
 
0.5%
2000014
 
0.5%
Other values (81)197
 
6.5%
(Missing)2479
82.4%
ValueCountFrequency (%)
0123
4.1%
15
 
0.2%
102
 
0.1%
231
 
< 0.1%
2001
 
< 0.1%
3004
 
0.1%
6001
 
< 0.1%
8001
 
< 0.1%
10006
 
0.2%
12001
 
< 0.1%
ValueCountFrequency (%)
800002
0.1%
600001
 
< 0.1%
550003
0.1%
480001
 
< 0.1%
470001
 
< 0.1%
460001
 
< 0.1%
450001
 
< 0.1%
430001
 
< 0.1%
370001
 
< 0.1%
360003
0.1%

Yearly stocks
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct61
Distinct (%)30.0%
Missing2806
Missing (%)93.3%
Infinite0
Infinite (%)0.0%
Mean18263.1198
Minimum0
Maximum750000
Zeros31
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum0
5-th percentile0
Q11
median2000
Q320000
95-th percentile71300
Maximum750000
Range750000
Interquartile range (IQR)19999

Descriptive statistics

Standard deviation61012.38777
Coefficient of variation (CV)3.340742898
Kurtosis107.0964767
Mean18263.1198
Median Absolute Deviation (MAD)2000
Skewness9.526380439
Sum3707413.32
Variance3722511462
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
143
 
1.4%
031
 
1.0%
100008
 
0.3%
20008
 
0.3%
250007
 
0.2%
500006
 
0.2%
50006
 
0.2%
30006
 
0.2%
300005
 
0.2%
200005
 
0.2%
Other values (51)78
 
2.6%
(Missing)2806
93.3%
ValueCountFrequency (%)
031
1.0%
0.012
 
0.1%
0.13
 
0.1%
143
1.4%
51
 
< 0.1%
101
 
< 0.1%
301
 
< 0.1%
501
 
< 0.1%
1001
 
< 0.1%
1251
 
< 0.1%
ValueCountFrequency (%)
7500001
< 0.1%
3500001
< 0.1%
1400001
< 0.1%
1170001
< 0.1%
1000001
< 0.1%
900001
< 0.1%
840001
< 0.1%
800001
< 0.1%
750001
< 0.1%
720002
0.1%

Yearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same country
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct128
Distinct (%)21.2%
Missing2406
Missing (%)80.0%
Infinite0
Infinite (%)0.0%
Mean65803.89552
Minimum0
Maximum200000
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum0
5-th percentile38100
Q155000
median65000
Q375000
95-th percentile99900
Maximum200000
Range200000
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation20554.01761
Coefficient of variation (CV)0.3123525963
Kurtosis5.331724798
Mean65803.89552
Median Absolute Deviation (MAD)10000
Skewness1.032919331
Sum39679749
Variance422467640.1
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000049
 
1.6%
6500038
 
1.3%
5500038
 
1.3%
7500033
 
1.1%
7000032
 
1.1%
6600017
 
0.6%
8000015
 
0.5%
5000014
 
0.5%
5200014
 
0.5%
7200013
 
0.4%
Other values (118)340
 
11.3%
(Missing)2406
80.0%
ValueCountFrequency (%)
01
< 0.1%
11
< 0.1%
581
< 0.1%
72001
< 0.1%
90001
< 0.1%
100001
< 0.1%
170001
< 0.1%
196001
< 0.1%
200002
0.1%
227301
< 0.1%
ValueCountFrequency (%)
2000001
 
< 0.1%
1600002
 
0.1%
1460001
 
< 0.1%
1440001
 
< 0.1%
1300002
 
0.1%
1270001
 
< 0.1%
1200002
 
0.1%
1170001
 
< 0.1%
1150005
0.2%
1140001
 
< 0.1%

Yearly bonus one year ago. Only answer if staying in same country
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct64
Distinct (%)24.9%
Missing2752
Missing (%)91.5%
Infinite0
Infinite (%)0.0%
Mean8144
Minimum0
Maximum150000
Zeros23
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum0
5-th percentile0
Q11000
median5000
Q39000
95-th percentile26000
Maximum150000
Range150000
Interquartile range (IQR)8000

Descriptive statistics

Standard deviation15067.8767
Coefficient of variation (CV)1.850181324
Kurtosis43.01728724
Mean8144
Median Absolute Deviation (MAD)4000
Skewness5.754762713
Sum2093008
Variance227040908.3
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500027
 
0.9%
126
 
0.9%
023
 
0.8%
300017
 
0.6%
1000017
 
0.6%
800012
 
0.4%
600012
 
0.4%
400010
 
0.3%
120009
 
0.3%
70009
 
0.3%
Other values (54)95
 
3.2%
(Missing)2752
91.5%
ValueCountFrequency (%)
023
0.8%
126
0.9%
161
 
< 0.1%
351
 
< 0.1%
2001
 
< 0.1%
3002
 
0.1%
5004
 
0.1%
8001
 
< 0.1%
9001
 
< 0.1%
10005
 
0.2%
ValueCountFrequency (%)
1500001
 
< 0.1%
1180001
 
< 0.1%
730001
 
< 0.1%
600001
 
< 0.1%
590001
 
< 0.1%
500002
0.1%
450001
 
< 0.1%
435001
 
< 0.1%
350001
 
< 0.1%
300003
0.1%

Yearly stocks one year ago. Only answer if staying in same country
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct31
Distinct (%)22.3%
Missing2870
Missing (%)95.4%
Infinite0
Infinite (%)0.0%
Mean8204.476331
Minimum0
Maximum520000
Zeros68
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.1
Q33000
95-th percentile20500
Maximum520000
Range520000
Interquartile range (IQR)3000

Descriptive statistics

Standard deviation45224.39737
Coefficient of variation (CV)5.512161356
Kurtosis121.1445566
Mean8204.476331
Median Absolute Deviation (MAD)0.1
Skewness10.70644724
Sum1140422.21
Variance2045246118
MonotonicityNot monotonic
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
068
 
2.3%
119
 
0.6%
100008
 
0.3%
150005
 
0.2%
30004
 
0.1%
200004
 
0.1%
50004
 
0.1%
20002
 
0.1%
500002
 
0.1%
0.12
 
0.1%
Other values (21)21
 
0.7%
(Missing)2870
95.4%
ValueCountFrequency (%)
068
2.3%
0.011
 
< 0.1%
0.12
 
0.1%
119
 
0.6%
51
 
< 0.1%
101
 
< 0.1%
381
 
< 0.1%
1001
 
< 0.1%
3501
 
< 0.1%
3601
 
< 0.1%
ValueCountFrequency (%)
5200001
 
< 0.1%
800001
 
< 0.1%
600001
 
< 0.1%
500002
 
0.1%
370001
 
< 0.1%
250001
 
< 0.1%
200004
0.1%
182401
 
< 0.1%
150005
0.2%
120001
 
< 0.1%

Number of home office days per month
Real number (ℝ≥0)

HIGH CORRELATION
MISSING
ZEROS

Distinct21
Distinct (%)3.3%
Missing2370
Missing (%)78.8%
Infinite0
Infinite (%)0.0%
Mean6.462050078
Minimum0
Maximum365
Zeros101
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q37
95-th percentile20
Maximum365
Range365
Interquartile range (IQR)5

Descriptive statistics

Standard deviation15.38460138
Coefficient of variation (CV)2.380761708
Kurtosis463.7945219
Mean6.462050078
Median Absolute Deviation (MAD)2
Skewness19.97055126
Sum4129.25
Variance236.6859596
MonotonicityNot monotonic
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
4162
 
5.4%
0101
 
3.4%
5101
 
3.4%
2065
 
2.2%
247
 
1.6%
1034
 
1.1%
830
 
1.0%
126
 
0.9%
323
 
0.8%
1516
 
0.5%
Other values (11)34
 
1.1%
(Missing)2370
78.8%
ValueCountFrequency (%)
0101
3.4%
0.251
 
< 0.1%
126
 
0.9%
247
 
1.6%
323
 
0.8%
4162
5.4%
5101
3.4%
612
 
0.4%
710
 
0.3%
830
 
1.0%
ValueCountFrequency (%)
3651
 
< 0.1%
301
 
< 0.1%
251
 
< 0.1%
241
 
< 0.1%
2065
2.2%
161
 
< 0.1%
1516
 
0.5%
141
 
< 0.1%
122
 
0.1%
1034
1.1%

Company name
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct220
Distinct (%)85.6%
Missing2752
Missing (%)91.5%
Memory size23.6 KiB
Zalando
 
7
Auto1
 
5
Booking.com
 
4
Sixt
 
3
ING
 
3
Other values (215)
235 

Length

Max length46
Median length7
Mean length9.311284047
Min length1

Characters and Unicode

Total characters2393
Distinct characters71
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)76.7%

Sample

1st rowAuto1
2nd rowLuxoft
3rd rowZalando
4th rowBonial International GmbH
5th rowFootball app

Common Values

ValueCountFrequency (%)
Zalando7
 
0.2%
Auto15
 
0.2%
Booking.com4
 
0.1%
Sixt3
 
0.1%
ING3
 
0.1%
Luxoft3
 
0.1%
SAP3
 
0.1%
Ingenico2
 
0.1%
Yandex2
 
0.1%
Here2
 
0.1%
Other values (210)223
 
7.4%
(Missing)2752
91.5%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
gmbh22
 
6.2%
auto19
 
2.5%
zalando7
 
2.0%
group7
 
2.0%
booking.com4
 
1.1%
check244
 
1.1%
ing4
 
1.1%
ag4
 
1.1%
digital3
 
0.8%
scout243
 
0.8%
Other values (246)287
81.1%

Most occurring characters

ValueCountFrequency (%)
e196
 
8.2%
o163
 
6.8%
a155
 
6.5%
n140
 
5.9%
t135
 
5.6%
i128
 
5.3%
r121
 
5.1%
115
 
4.8%
s89
 
3.7%
l88
 
3.7%
Other values (61)1063
44.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1747
73.0%
Uppercase Letter476
 
19.9%
Space Separator115
 
4.8%
Decimal Number34
 
1.4%
Other Punctuation15
 
0.6%
Dash Punctuation6
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A46
 
9.7%
S46
 
9.7%
G43
 
9.0%
H32
 
6.7%
I29
 
6.1%
T28
 
5.9%
E24
 
5.0%
C23
 
4.8%
B21
 
4.4%
D21
 
4.4%
Other values (20)163
34.2%
Lowercase Letter
ValueCountFrequency (%)
e196
11.2%
o163
 
9.3%
a155
 
8.9%
n140
 
8.0%
t135
 
7.7%
i128
 
7.3%
r121
 
6.9%
s89
 
5.1%
l88
 
5.0%
c73
 
4.2%
Other values (20)459
26.3%
Decimal Number
ValueCountFrequency (%)
116
47.1%
27
20.6%
47
20.6%
32
 
5.9%
61
 
2.9%
01
 
2.9%
Other Punctuation
ValueCountFrequency (%)
.9
60.0%
&4
26.7%
/2
 
13.3%
Space Separator
ValueCountFrequency (%)
115
100.0%
Dash Punctuation
ValueCountFrequency (%)
-6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2213
92.5%
Common170
 
7.1%
Cyrillic10
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e196
 
8.9%
o163
 
7.4%
a155
 
7.0%
n140
 
6.3%
t135
 
6.1%
i128
 
5.8%
r121
 
5.5%
s89
 
4.0%
l88
 
4.0%
c73
 
3.3%
Other values (41)925
41.8%
Common
ValueCountFrequency (%)
115
67.6%
116
 
9.4%
.9
 
5.3%
27
 
4.1%
47
 
4.1%
-6
 
3.5%
&4
 
2.4%
/2
 
1.2%
32
 
1.2%
61
 
0.6%
Cyrillic
ValueCountFrequency (%)
ф2
20.0%
Я1
10.0%
д1
10.0%
т1
10.0%
в1
10.0%
щ1
10.0%
С1
10.0%
П1
10.0%
Ш1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2382
99.5%
Cyrillic10
 
0.4%
Latin 1 Sup1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e196
 
8.2%
o163
 
6.8%
a155
 
6.5%
n140
 
5.9%
t135
 
5.7%
i128
 
5.4%
r121
 
5.1%
115
 
4.8%
s89
 
3.7%
l88
 
3.7%
Other values (51)1052
44.2%
Cyrillic
ValueCountFrequency (%)
ф2
20.0%
Я1
10.0%
д1
10.0%
т1
10.0%
в1
10.0%
щ1
10.0%
С1
10.0%
П1
10.0%
Ш1
10.0%
Latin 1 Sup
ValueCountFrequency (%)
ó1
100.0%

Company business sector
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct52
Distinct (%)6.1%
Missing2163
Missing (%)71.9%
Memory size23.6 KiB
Сommerce
205 
Finance / Insurance
163 
Transport
86 
Manufacture
53 
IT
44 
Other values (47)
295 

Length

Max length23
Median length9
Mean length10.88179669
Min length2

Characters and Unicode

Total characters9206
Distinct characters45
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)2.2%

Sample

1st rowTourism
2nd rowScientific Activities
3rd rowTransport
4th rowAutomotive
5th rowСommerce

Common Values

ValueCountFrequency (%)
Сommerce205
 
6.8%
Finance / Insurance163
 
5.4%
Transport86
 
2.9%
Manufacture53
 
1.8%
IT44
 
1.5%
Health37
 
1.2%
Tourism36
 
1.2%
Software Development30
 
1.0%
Scientific Activities24
 
0.8%
Telecom19
 
0.6%
Other values (42)149
 
5.0%
(Missing)2163
71.9%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
сommerce205
16.4%
163
13.1%
insurance163
13.1%
finance163
13.1%
transport86
 
6.9%
manufacture53
 
4.2%
it44
 
3.5%
health37
 
3.0%
tourism36
 
2.9%
software31
 
2.5%
Other values (54)268
21.5%

Most occurring characters

ValueCountFrequency (%)
e1144
12.4%
n950
 
10.3%
r719
 
7.8%
c712
 
7.7%
a683
 
7.4%
m528
 
5.7%
o489
 
5.3%
i473
 
5.1%
t455
 
4.9%
405
 
4.4%
Other values (35)2648
28.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7490
81.4%
Uppercase Letter1145
 
12.4%
Space Separator405
 
4.4%
Other Punctuation164
 
1.8%
Dash Punctuation2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1144
15.3%
n950
12.7%
r719
9.6%
c712
9.5%
a683
9.1%
m528
7.0%
o489
6.5%
i473
6.3%
t455
 
6.1%
s363
 
4.8%
Other values (12)974
13.0%
Uppercase Letter
ValueCountFrequency (%)
С213
18.6%
I213
18.6%
T193
16.9%
F168
14.7%
M72
 
6.3%
S64
 
5.6%
A52
 
4.5%
H42
 
3.7%
D37
 
3.2%
E30
 
2.6%
Other values (9)61
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/163
99.4%
,1
 
0.6%
Space Separator
ValueCountFrequency (%)
405
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8422
91.5%
Common571
 
6.2%
Cyrillic213
 
2.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1144
13.6%
n950
11.3%
r719
 
8.5%
c712
 
8.5%
a683
 
8.1%
m528
 
6.3%
o489
 
5.8%
i473
 
5.6%
t455
 
5.4%
s363
 
4.3%
Other values (30)1906
22.6%
Common
ValueCountFrequency (%)
405
70.9%
/163
28.5%
-2
 
0.4%
,1
 
0.2%
Cyrillic
ValueCountFrequency (%)
С213
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8993
97.7%
Cyrillic213
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e1144
12.7%
n950
 
10.6%
r719
 
8.0%
c712
 
7.9%
a683
 
7.6%
m528
 
5.9%
o489
 
5.4%
i473
 
5.3%
t455
 
5.1%
405
 
4.5%
Other values (34)2435
27.1%
Cyrillic
ValueCountFrequency (%)
С213
100.0%

0
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing3009
Missing (%)100.0%
Memory size23.6 KiB

Position
Categorical

HIGH CARDINALITY
MISSING

Distinct397
Distinct (%)53.9%
Missing2272
Missing (%)75.5%
Memory size23.6 KiB
Java Developer
 
34
Software Engineer
 
29
Senior Software Engineer
 
16
QA
 
15
Software Developer
 
13
Other values (392)
630 

Length

Max length48
Median length16
Mean length16.01899593
Min length2

Characters and Unicode

Total characters11806
Distinct characters79
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)40.4%

Sample

1st rowQA Ingenieur
2nd rowSenior PHP Magento developer
3rd rowSoftware Engineer
4th rowSenior Frontend Developer
5th rowUX Designer

Common Values

ValueCountFrequency (%)
Java Developer34
 
1.1%
Software Engineer29
 
1.0%
Senior Software Engineer16
 
0.5%
QA15
 
0.5%
Software Developer13
 
0.4%
Frontend Developer13
 
0.4%
iOS Developer12
 
0.4%
Data Scientist11
 
0.4%
DevOps11
 
0.4%
Android Developer8
 
0.3%
Other values (387)575
 
19.1%
(Missing)2272
75.5%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
developer302
18.7%
engineer157
 
9.7%
software124
 
7.7%
senior96
 
5.9%
java66
 
4.1%
qa43
 
2.7%
data35
 
2.2%
c33
 
2.0%
devops32
 
2.0%
manager32
 
2.0%
Other values (200)696
43.1%

Most occurring characters

ValueCountFrequency (%)
e1946
16.5%
r960
 
8.1%
944
 
8.0%
n771
 
6.5%
o733
 
6.2%
a667
 
5.6%
t529
 
4.5%
i528
 
4.5%
l449
 
3.8%
v433
 
3.7%
Other values (69)3846
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter9033
76.5%
Uppercase Letter1684
 
14.3%
Space Separator944
 
8.0%
Other Punctuation60
 
0.5%
Math Symbol40
 
0.3%
Open Punctuation14
 
0.1%
Close Punctuation14
 
0.1%
Dash Punctuation11
 
0.1%
Decimal Number6
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1946
21.5%
r960
10.6%
n771
 
8.5%
o733
 
8.1%
a667
 
7.4%
t529
 
5.9%
i528
 
5.8%
l449
 
5.0%
v433
 
4.8%
p383
 
4.2%
Other values (30)1634
18.1%
Uppercase Letter
ValueCountFrequency (%)
S334
19.8%
D315
18.7%
E179
10.6%
A114
 
6.8%
P108
 
6.4%
J82
 
4.9%
T68
 
4.0%
O63
 
3.7%
C61
 
3.6%
F60
 
3.6%
Other values (14)300
17.8%
Other Punctuation
ValueCountFrequency (%)
.26
43.3%
/17
28.3%
#14
23.3%
&1
 
1.7%
\1
 
1.7%
,1
 
1.7%
Decimal Number
ValueCountFrequency (%)
22
33.3%
32
33.3%
11
16.7%
01
16.7%
Space Separator
ValueCountFrequency (%)
944
100.0%
Dash Punctuation
ValueCountFrequency (%)
-11
100.0%
Open Punctuation
ValueCountFrequency (%)
(14
100.0%
Close Punctuation
ValueCountFrequency (%)
)14
100.0%
Math Symbol
ValueCountFrequency (%)
+40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin10696
90.6%
Common1089
 
9.2%
Cyrillic21
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1946
18.2%
r960
 
9.0%
n771
 
7.2%
o733
 
6.9%
a667
 
6.2%
t529
 
4.9%
i528
 
4.9%
l449
 
4.2%
v433
 
4.0%
p383
 
3.6%
Other values (38)3297
30.8%
Cyrillic
ValueCountFrequency (%)
у3
14.3%
е2
 
9.5%
с2
 
9.5%
и2
 
9.5%
в1
 
4.8%
м1
 
4.8%
д1
 
4.8%
щ1
 
4.8%
з1
 
4.8%
к1
 
4.8%
Other values (6)6
28.6%
Common
ValueCountFrequency (%)
944
86.7%
+40
 
3.7%
.26
 
2.4%
/17
 
1.6%
(14
 
1.3%
)14
 
1.3%
#14
 
1.3%
-11
 
1.0%
22
 
0.2%
32
 
0.2%
Other values (5)5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII11785
99.8%
Cyrillic21
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e1946
16.5%
r960
 
8.1%
944
 
8.0%
n771
 
6.5%
o733
 
6.2%
a667
 
5.7%
t529
 
4.5%
i528
 
4.5%
l449
 
3.8%
v433
 
3.7%
Other values (53)3825
32.5%
Cyrillic
ValueCountFrequency (%)
у3
14.3%
е2
 
9.5%
с2
 
9.5%
и2
 
9.5%
в1
 
4.8%
м1
 
4.8%
д1
 
4.8%
щ1
 
4.8%
з1
 
4.8%
к1
 
4.8%
Other values (6)6
28.6%

Your level
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)0.4%
Missing2266
Missing (%)75.3%
Memory size23.6 KiB
Senior
497 
Middle
206 
Junior
 
40

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters4458
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSenior
2nd rowSenior
3rd rowSenior
4th rowSenior
5th rowSenior

Common Values

ValueCountFrequency (%)
Senior497
 
16.5%
Middle206
 
6.8%
Junior40
 
1.3%
(Missing)2266
75.3%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
senior497
66.9%
middle206
27.7%
junior40
 
5.4%

Most occurring characters

ValueCountFrequency (%)
i743
16.7%
e703
15.8%
n537
12.0%
o537
12.0%
r537
12.0%
S497
11.1%
d412
9.2%
M206
 
4.6%
l206
 
4.6%
J40
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3715
83.3%
Uppercase Letter743
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i743
20.0%
e703
18.9%
n537
14.5%
o537
14.5%
r537
14.5%
d412
11.1%
l206
 
5.5%
u40
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
S497
66.9%
M206
27.7%
J40
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
Latin4458
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i743
16.7%
e703
15.8%
n537
12.0%
o537
12.0%
r537
12.0%
S497
11.1%
d412
9.2%
M206
 
4.6%
l206
 
4.6%
J40
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII4458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i743
16.7%
e703
15.8%
n537
12.0%
o537
12.0%
r537
12.0%
S497
11.1%
d412
9.2%
M206
 
4.6%
l206
 
4.6%
J40
 
0.9%

Current Salary
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct139
Distinct (%)18.5%
Missing2259
Missing (%)75.1%
Infinite0
Infinite (%)0.0%
Mean68381.76533
Minimum10300
Maximum200000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum10300
5-th percentile40000
Q157000
median65000
Q375000
95-th percentile110000
Maximum200000
Range189700
Interquartile range (IQR)18000

Descriptive statistics

Standard deviation21196.30656
Coefficient of variation (CV)0.3099701573
Kurtosis5.178434622
Mean68381.76533
Median Absolute Deviation (MAD)10000
Skewness1.414854159
Sum51286324
Variance449283411.7
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000073
 
2.4%
6500068
 
2.3%
7000050
 
1.7%
7500043
 
1.4%
5500030
 
1.0%
8000028
 
0.9%
7200023
 
0.8%
5000020
 
0.7%
6800020
 
0.7%
9000019
 
0.6%
Other values (129)376
 
12.5%
(Missing)2259
75.1%
ValueCountFrequency (%)
103001
 
< 0.1%
130001
 
< 0.1%
150001
 
< 0.1%
175321
 
< 0.1%
192001
 
< 0.1%
204001
 
< 0.1%
231621
 
< 0.1%
240004
0.1%
270001
 
< 0.1%
300005
0.2%
ValueCountFrequency (%)
2000001
 
< 0.1%
1800001
 
< 0.1%
1760001
 
< 0.1%
1650001
 
< 0.1%
1500001
 
< 0.1%
1400002
 
0.1%
1380001
 
< 0.1%
1322501
 
< 0.1%
1320001
 
< 0.1%
1300006
0.2%

Salary one year ago
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct125
Distinct (%)21.0%
Missing2413
Missing (%)80.2%
Infinite0
Infinite (%)0.0%
Mean62187.27852
Minimum10001
Maximum200000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum10001
5-th percentile30000
Q152000
median60000
Q370000
95-th percentile95250
Maximum200000
Range189999
Interquartile range (IQR)18000

Descriptive statistics

Standard deviation20163.00866
Coefficient of variation (CV)0.3242304398
Kurtosis4.720050742
Mean62187.27852
Median Absolute Deviation (MAD)10000
Skewness0.9022019418
Sum37063618
Variance406546918.3
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6500057
 
1.9%
5500048
 
1.6%
6000042
 
1.4%
7000026
 
0.9%
5000024
 
0.8%
7500019
 
0.6%
5800018
 
0.6%
8000018
 
0.6%
4500015
 
0.5%
6800015
 
0.5%
Other values (115)314
 
10.4%
(Missing)2413
80.2%
ValueCountFrequency (%)
100011
< 0.1%
103001
< 0.1%
105002
0.1%
108001
< 0.1%
115201
< 0.1%
120001
< 0.1%
130001
< 0.1%
140001
< 0.1%
144001
< 0.1%
165001
< 0.1%
ValueCountFrequency (%)
2000001
 
< 0.1%
1300002
 
0.1%
1290001
 
< 0.1%
1250002
 
0.1%
1240001
 
< 0.1%
1230001
 
< 0.1%
1200003
0.1%
1190001
 
< 0.1%
1150002
 
0.1%
1100005
0.2%

Salary two years ago
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct105
Distinct (%)22.7%
Missing2546
Missing (%)84.6%
Infinite0
Infinite (%)0.0%
Mean58013.47516
Minimum10001
Maximum150000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB

Quantile statistics

Minimum10001
5-th percentile22200
Q148000
median56000
Q367000
95-th percentile95000
Maximum150000
Range139999
Interquartile range (IQR)19000

Descriptive statistics

Standard deviation20413.04891
Coefficient of variation (CV)0.3518673696
Kurtosis1.95291779
Mean58013.47516
Median Absolute Deviation (MAD)10000
Skewness0.5754506612
Sum26860239
Variance416692565.7
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000038
 
1.3%
5500036
 
1.2%
6500031
 
1.0%
5000030
 
1.0%
7000017
 
0.6%
4500016
 
0.5%
4000016
 
0.5%
5400014
 
0.5%
4800014
 
0.5%
7500013
 
0.4%
Other values (95)238
 
7.9%
(Missing)2546
84.6%
ValueCountFrequency (%)
100014
0.1%
103001
 
< 0.1%
105001
 
< 0.1%
108002
0.1%
120001
 
< 0.1%
130002
0.1%
150003
0.1%
160001
 
< 0.1%
165001
 
< 0.1%
170001
 
< 0.1%
ValueCountFrequency (%)
1500001
< 0.1%
1300001
< 0.1%
1250001
< 0.1%
1240001
< 0.1%
1200002
0.1%
1190001
< 0.1%
1180001
< 0.1%
1150002
0.1%
1100001
< 0.1%
1050002
0.1%
Distinct2
Distinct (%)0.3%
Missing2267
Missing (%)75.3%
Memory size6.0 KiB
False
587 
True
 
155
(Missing)
2267 
ValueCountFrequency (%)
False587
 
19.5%
True155
 
5.2%
(Missing)2267
75.3%

Interactions

Correlations

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

df_indexTimestampAgeGenderCityPositionTotal years of experienceYears of experience in GermanySeniority levelYour main technology / programming languageOther technologies/programming languages you use oftenYearly brutto salary (without bonus and stocks) in EURYearly bonus + stocks in EURAnnual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same countryAnnual bonus+stocks one year ago. Only answer if staying in same countryNumber of vacation daysEmployment statusСontract durationMain language at workCompany sizeCompany typeHave you lost your job due to the coronavirus outbreak?Have you been forced to have a shorter working week (Kurzarbeit)? If yes, how many hours per weekHave you received additional monetary support from your employer due to Work From Home? If yes, how much in 2020 in EURZeitstempelPosition (without seniority)Years of experienceYearly brutto salary (without bonus and stocks)Yearly bonusYearly stocksYearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same countryYearly bonus one year ago. Only answer if staying in same countryYearly stocks one year ago. Only answer if staying in same countryNumber of home office days per monthCompany nameCompany business sector0PositionYour levelCurrent SalarySalary one year agoSalary two years agoAre you getting any Stock Options?
0024/11/2020 11:14:1526.0MaleMunichSoftware Engineer53SeniorTypeScriptKotlin, Javascript / Typescript80000.0500075000.01000030Full-time employeeUnlimited contractEnglish51-100ProductNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1124/11/2020 11:14:1626.0MaleBerlinBackend Developer74SeniorRubyNaN80000.0NaN82000.0500028Full-time employeeUnlimited contractEnglish101-1000ProductNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2224/11/2020 11:14:2129.0MaleBerlinSoftware Engineer126LeadJavascript / TypescriptJavascript / Typescript, Docker120000.0120000100000.010000030Self-employed (freelancer)Temporary contractEnglish101-1000ProductYesNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3324/11/2020 11:15:2428.0MaleBerlinFrontend Developer41JuniorJavascriptNaN54000.0NaNNaNNaN24Full-time employeeUnlimited contractEnglish51-100StartupNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4424/11/2020 11:15:4637.0MaleBerlinBackend Developer176SeniorC# .NET.NET, SQL, AWS, Docker62000.0NaN62000.0NaN29Full-time employeeUnlimited contractEnglish101-1000ProductNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
5524/11/2020 11:15:5332.0MaleBerlinDevOps51SeniorAWS, GCP, Python,K8sPython, AWS, Google Cloud, Kubernetes, Docker76000.0500076000.0500030Full-time employeeUnlimited contractEnglish11-50StartupNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
6624/11/2020 11:16:3537.0MaleBerlinFrontend Developer60.4MiddleJavascriptNaN57000.0NaNNaNNaN24Full-time employeeUnlimited contractEnglish11-50ProductNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
7724/11/2020 11:16:4424.0MaleBerlinFrontend Developer51SeniorTypescriptJavascript / Typescript65000.0NaN65000.0NaN27Full-time employeeUnlimited contractEnglish1000+ProductNo0.0600NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
8824/11/2020 11:17:2429.0MaleBerlinBackend Developer82SeniorPHPSQL, AWS, Docker56000.0NaN55000.0NaN28Full-time employeeUnlimited contractEnglish101-1000ProductNo30.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
9924/11/2020 11:17:5035.0MaleBerlinSoftware Engineer153LeadJavaNaN95000.0NaN90000.0NaN30Full-time employeeUnlimited contractEnglish101-1000ProductNo0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Last rows

df_indexTimestampAgeGenderCityPositionTotal years of experienceYears of experience in GermanySeniority levelYour main technology / programming languageOther technologies/programming languages you use oftenYearly brutto salary (without bonus and stocks) in EURYearly bonus + stocks in EURAnnual brutto salary (without bonus and stocks) one year ago. Only answer if staying in the same countryAnnual bonus+stocks one year ago. Only answer if staying in same countryNumber of vacation daysEmployment statusСontract durationMain language at workCompany sizeCompany typeHave you lost your job due to the coronavirus outbreak?Have you been forced to have a shorter working week (Kurzarbeit)? If yes, how many hours per weekHave you received additional monetary support from your employer due to Work From Home? If yes, how much in 2020 in EURZeitstempelPosition (without seniority)Years of experienceYearly brutto salary (without bonus and stocks)Yearly bonusYearly stocksYearly brutto salary (without bonus and stocks) one year ago. Only answer if staying in same countryYearly bonus one year ago. Only answer if staying in same countryYearly stocks one year ago. Only answer if staying in same countryNumber of home office days per monthCompany nameCompany business sector0PositionYour levelCurrent SalarySalary one year agoSalary two years agoAre you getting any Stock Options?
299975506/01/2020 13:38:0530.0MMünchenNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNDeutsch100-1000AgencyNaNNaNNaNNaNNaN10.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNSoftwareentwicklerMiddle75000.050000.0NaNNo
300075605/03/2020 16:50:4352.0MKölnNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNEnglish1000+AgencyNaNNaNNaNNaNNaN30.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNIT EngineerMiddle63000.080000.080000.0No
300175711/03/2020 23:23:19NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
300275831/05/2020 16:28:15NaNMBerlinNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
300375931/05/2020 16:28:23NaNMBerlinNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
300476003/06/2020 20:12:5140.0MKölnNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNDeutsch10-50ProductNaNNaNNaNNaNNaN1.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJava Developer juniorJunior44000.040000.040000.0Yes
300576128/07/2020 04:03:13NaNMKölnNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNDeutsch10-50ProductNaNNaNNaNNaNNaN1.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNE.g. C# DeveloperJunior45000.040000.040000.0Yes
300676228/07/2020 04:03:20NaNMKölnNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNDeutsch10-50ProductNaNNaNNaNNaNNaN1.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNE.g. C# DeveloperJunior45000.040000.040000.0Yes
300776326/08/2020 09:06:44NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
300876421/09/2020 01:47:1031.0FMünchenNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNEnglish1000+ProductNaNNaNNaNNaNNaN10.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPmSenior110000.0NaNNaNNo